- a(double) - Method in class org.deeplearning4j.nn.conf.dropout.AlphaDropout
-
- absPath - Variable in class org.deeplearning4j.text.documentiterator.FilenamesLabelAwareIterator
-
- AbstractCache<T extends SequenceElement> - Class in org.deeplearning4j.models.word2vec.wordstore.inmemory
-
This is generic VocabCache implementation designed as abstract SequenceElements vocabulary
- AbstractCache() - Constructor for class org.deeplearning4j.models.word2vec.wordstore.inmemory.AbstractCache
-
- AbstractCache.Builder<T extends SequenceElement> - Class in org.deeplearning4j.models.word2vec.wordstore.inmemory
-
- AbstractCoOccurrences<T extends SequenceElement> - Class in org.deeplearning4j.models.glove
-
This class implements building cooccurrence map for abstract training corpus.
- AbstractCoOccurrences.Builder<T extends SequenceElement> - Class in org.deeplearning4j.models.glove
-
- AbstractDataSetIterator<T> - Class in org.deeplearning4j.datasets.iterator
-
This is simple DataSetIterator implementation, that builds DataSetIterator out of INDArray/float[]/double[] pairs.
- AbstractDataSetIterator(Iterable<Pair<T, T>>, int) - Constructor for class org.deeplearning4j.datasets.iterator.AbstractDataSetIterator
-
- AbstractElementFactory<T extends SequenceElement> - Class in org.deeplearning4j.models.sequencevectors.serialization
-
This is universal serialization/deserialization factor for SequenceVectors serialization.
- AbstractElementFactory(Class<? extends SequenceElement>) - Constructor for class org.deeplearning4j.models.sequencevectors.serialization.AbstractElementFactory
-
This is the only constructor available for AbstractElementFactory
- AbstractLayer<LayerConfT extends Layer> - Class in org.deeplearning4j.nn.layers
-
A layer with input and output, no parameters or gradients
- AbstractLayer(NeuralNetConfiguration) - Constructor for class org.deeplearning4j.nn.layers.AbstractLayer
-
- AbstractLayer(NeuralNetConfiguration, INDArray) - Constructor for class org.deeplearning4j.nn.layers.AbstractLayer
-
- AbstractLSTM - Class in org.deeplearning4j.nn.conf.layers
-
LSTM recurrent net, based on Graves: Supervised Sequence Labelling with Recurrent Neural Networks
http://www.cs.toronto.edu/~graves/phd.pdf
- AbstractLSTM(AbstractLSTM.Builder) - Constructor for class org.deeplearning4j.nn.conf.layers.AbstractLSTM
-
- AbstractLSTM.Builder<T extends AbstractLSTM.Builder<T>> - Class in org.deeplearning4j.nn.conf.layers
-
- AbstractSameDiffLayer - Class in org.deeplearning4j.nn.conf.layers.samediff
-
- AbstractSameDiffLayer(AbstractSameDiffLayer.Builder) - Constructor for class org.deeplearning4j.nn.conf.layers.samediff.AbstractSameDiffLayer
-
- AbstractSameDiffLayer() - Constructor for class org.deeplearning4j.nn.conf.layers.samediff.AbstractSameDiffLayer
-
- AbstractSameDiffLayer.Builder<T extends AbstractSameDiffLayer.Builder<T>> - Class in org.deeplearning4j.nn.conf.layers.samediff
-
- AbstractSequenceIterator<T extends SequenceElement> - Class in org.deeplearning4j.models.sequencevectors.iterators
-
This is basic generic SequenceIterator implementation
- AbstractSequenceIterator(Iterable<Sequence<T>>) - Constructor for class org.deeplearning4j.models.sequencevectors.iterators.AbstractSequenceIterator
-
- AbstractSequenceIterator.Builder<T extends SequenceElement> - Class in org.deeplearning4j.models.sequencevectors.iterators
-
- AbstractVertexFactory<T extends SequenceElement> - Class in org.deeplearning4j.models.sequencevectors.graph.vertex
-
VertexFactory implementation
- AbstractVertexFactory() - Constructor for class org.deeplearning4j.models.sequencevectors.graph.vertex.AbstractVertexFactory
-
- ACCESS_KEY - Static variable in class org.deeplearning4j.aws.s3.BaseS3
-
- ACCESS_SECRET - Static variable in class org.deeplearning4j.aws.s3.BaseS3
-
- accessKey - Variable in class org.deeplearning4j.aws.s3.BaseS3
-
- accumulateScore(double) - Method in interface org.deeplearning4j.nn.api.Model
-
Sets a rolling tally for the score.
- accumulateScore(double) - Method in class org.deeplearning4j.nn.graph.ComputationGraph
-
- accumulateScore(double) - Method in class org.deeplearning4j.nn.layers.AbstractLayer
-
- accumulateScore(double) - Method in class org.deeplearning4j.nn.layers.BaseLayer
-
- accumulateScore(double) - Method in class org.deeplearning4j.nn.layers.convolution.SpaceToBatch
-
- accumulateScore(double) - Method in class org.deeplearning4j.nn.layers.convolution.SpaceToDepth
-
- accumulateScore(double) - Method in class org.deeplearning4j.nn.layers.convolution.subsampling.Subsampling3DLayer
-
- accumulateScore(double) - Method in class org.deeplearning4j.nn.layers.convolution.subsampling.SubsamplingLayer
-
- accumulateScore(double) - Method in class org.deeplearning4j.nn.layers.convolution.upsampling.Upsampling2D
-
- accumulateScore(double) - Method in class org.deeplearning4j.nn.layers.convolution.upsampling.Upsampling3D
-
- accumulateScore(double) - Method in class org.deeplearning4j.nn.layers.recurrent.BidirectionalLayer
-
- accumulateScore(double) - Method in class org.deeplearning4j.nn.layers.variational.VariationalAutoencoder
-
- accumulateScore(double) - Method in class org.deeplearning4j.nn.layers.wrapper.BaseWrapperLayer
-
- accumulateScore(double) - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
-
- accumulateScore(double) - Method in class org.deeplearning4j.plot.BarnesHutTsne
-
- accumulator - Variable in class org.deeplearning4j.optimize.solvers.accumulation.EncodedGradientsAccumulator
-
- accumulator - Variable in class org.deeplearning4j.optimize.solvers.accumulation.EncodingHandler
-
- accumulator - Variable in class org.deeplearning4j.optimize.solvers.accumulation.LocalHandler
-
- accumulator - Variable in class org.deeplearning4j.optimize.solvers.BaseOptimizer
-
- accumulator - Variable in class org.deeplearning4j.parallelism.ParallelWrapper.Builder
-
- accumulator - Variable in class org.deeplearning4j.parallelism.trainer.SymmetricTrainer
-
- accumulator - Variable in class org.deeplearning4j.spark.models.sequencevectors.functions.CountFunction
-
- accumulator - Variable in class org.deeplearning4j.spark.models.sequencevectors.functions.ExtraCountFunction
-
- accumulator - Variable in class org.deeplearning4j.spark.parameterserver.networking.SilentTrainingDriver
-
- accumulator - Variable in class org.deeplearning4j.spark.parameterserver.pw.SharedTrainingWrapper
-
- accuracy() - Method in class org.deeplearning4j.eval.Evaluation
-
Accuracy:
(TP + TN) / (P + N)
- accuracy(int) - Method in class org.deeplearning4j.eval.EvaluationBinary
-
Get the accuracy for the specified output
- accuracy(List<String>) - Method in class org.deeplearning4j.models.embeddings.reader.impl.BasicModelUtils
-
Accuracy based on questions which are a space separated list of strings
where the first word is the query word, the next 2 words are negative,
and the last word is the predicted word to be nearest
- accuracy(List<String>) - Method in interface org.deeplearning4j.models.embeddings.reader.ModelUtils
-
Accuracy based on questions which are a space separated list of strings
where the first word is the query word, the next 2 words are negative,
and the last word is the predicted word to be nearest
- accuracy(List<String>) - Method in interface org.deeplearning4j.models.embeddings.wordvectors.WordVectors
-
Accuracy based on questions which are a space separated list of strings
where the first word is the query word, the next 2 words are negative,
and the last word is the predicted word to be nearest
- accuracy(List<String>) - Method in class org.deeplearning4j.models.embeddings.wordvectors.WordVectorsImpl
-
Accuracy based on questions which are a space separated list of strings
where the first word is the query word, the next 2 words are negative,
and the last word is the predicted word to be nearest
- accuracy(List<String>) - Method in class org.deeplearning4j.models.word2vec.StaticWord2Vec
-
Accuracy based on questions which are a space separated list of strings
where the first word is the query word, the next 2 words are negative,
and the last word is the predicted word to be nearest
PLEASE NOTE: This method is not available in this implementation.
- actingBlockLength - Variable in class org.deeplearning4j.ui.stats.sbe.StaticInfoDecoder
-
- actingBlockLength() - Method in class org.deeplearning4j.ui.stats.sbe.StaticInfoDecoder.HwDeviceInfoGroupDecoder
-
- actingBlockLength() - Method in class org.deeplearning4j.ui.stats.sbe.StaticInfoDecoder.ModelParamNamesDecoder
-
- actingBlockLength() - Method in class org.deeplearning4j.ui.stats.sbe.StaticInfoDecoder.SwEnvironmentInfoDecoder
-
- actingBlockLength - Variable in class org.deeplearning4j.ui.stats.sbe.StaticInfoEncoder
-
- actingBlockLength - Variable in class org.deeplearning4j.ui.stats.sbe.StorageMetaDataDecoder
-
- actingBlockLength() - Method in class org.deeplearning4j.ui.stats.sbe.StorageMetaDataDecoder.ExtraMetaDataBytesDecoder
-
- actingBlockLength - Variable in class org.deeplearning4j.ui.stats.sbe.StorageMetaDataEncoder
-
- actingBlockLength - Variable in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder
-
- actingBlockLength() - Method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder.DataSetMetaDataBytesDecoder
-
- actingBlockLength() - Method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder.DataSetMetaDataBytesDecoder.MetaDataBytesDecoder
-
- actingBlockLength() - Method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder.GcStatsDecoder
-
- actingBlockLength() - Method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder.LayerNamesDecoder
-
- actingBlockLength() - Method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder.MemoryUseDecoder
-
- actingBlockLength() - Method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder.ParamNamesDecoder
-
- actingBlockLength() - Method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder.PerformanceDecoder
-
- actingBlockLength() - Method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder.PerParameterStatsDecoder
-
- actingBlockLength() - Method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder.PerParameterStatsDecoder.HistogramsDecoder
-
- actingBlockLength() - Method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder.PerParameterStatsDecoder.HistogramsDecoder.HistogramCountsDecoder
-
- actingBlockLength() - Method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder.PerParameterStatsDecoder.SummaryStatDecoder
-
- actingBlockLength - Variable in class org.deeplearning4j.ui.stats.sbe.UpdateEncoder
-
- actingVersion - Variable in class org.deeplearning4j.ui.stats.sbe.StaticInfoDecoder
-
- actingVersion - Variable in class org.deeplearning4j.ui.stats.sbe.StaticInfoEncoder
-
- actingVersion - Variable in class org.deeplearning4j.ui.stats.sbe.StorageMetaDataDecoder
-
- actingVersion - Variable in class org.deeplearning4j.ui.stats.sbe.StorageMetaDataEncoder
-
- actingVersion - Variable in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder
-
- actingVersion - Variable in class org.deeplearning4j.ui.stats.sbe.UpdateEncoder
-
- actionForMapPartition(JavaRDD) - Method in class org.deeplearning4j.spark.text.functions.CountCumSum
-
- activate(boolean, LayerWorkspaceMgr) - Method in interface org.deeplearning4j.nn.api.Layer
-
Perform forward pass and return the activations array with the last set input
- activate(INDArray, boolean, LayerWorkspaceMgr) - Method in interface org.deeplearning4j.nn.api.Layer
-
Perform forward pass and return the activations array with the specified input
- activate(INDArray, boolean, LayerWorkspaceMgr) - Method in class org.deeplearning4j.nn.layers.AbstractLayer
-
- activate(boolean, LayerWorkspaceMgr) - Method in class org.deeplearning4j.nn.layers.ActivationLayer
-
- activate(boolean, LayerWorkspaceMgr) - Method in class org.deeplearning4j.nn.layers.BaseLayer
-
- activate(INDArray, boolean, LayerWorkspaceMgr) - Method in class org.deeplearning4j.nn.layers.BaseOutputLayer
-
- activate(boolean, LayerWorkspaceMgr) - Method in class org.deeplearning4j.nn.layers.convolution.CnnLossLayer
-
- activate(boolean, LayerWorkspaceMgr) - Method in class org.deeplearning4j.nn.layers.convolution.Convolution1DLayer
-
- activate(INDArray, IActivation) - Method in interface org.deeplearning4j.nn.layers.convolution.ConvolutionHelper
-
- activate(boolean, LayerWorkspaceMgr) - Method in class org.deeplearning4j.nn.layers.convolution.ConvolutionLayer
-
- activate(boolean, LayerWorkspaceMgr) - Method in class org.deeplearning4j.nn.layers.convolution.Cropping1DLayer
-
- activate(boolean, LayerWorkspaceMgr) - Method in class org.deeplearning4j.nn.layers.convolution.Cropping2DLayer
-
- activate(boolean, LayerWorkspaceMgr) - Method in class org.deeplearning4j.nn.layers.convolution.Cropping3DLayer
-
- activate(INDArray, IActivation) - Method in class org.deeplearning4j.nn.layers.convolution.CudnnConvolutionHelper
-
- activate(boolean, LayerWorkspaceMgr) - Method in class org.deeplearning4j.nn.layers.convolution.Deconvolution2DLayer
-
- activate(boolean, LayerWorkspaceMgr) - Method in class org.deeplearning4j.nn.layers.convolution.DepthwiseConvolution2DLayer
-
- activate(boolean, LayerWorkspaceMgr) - Method in class org.deeplearning4j.nn.layers.convolution.SeparableConvolution2DLayer
-
- activate(boolean, LayerWorkspaceMgr) - Method in class org.deeplearning4j.nn.layers.convolution.SpaceToBatch
-
- activate(boolean, LayerWorkspaceMgr) - Method in class org.deeplearning4j.nn.layers.convolution.SpaceToDepth
-
- activate(INDArray, boolean, int[], int[], int[], PoolingType, ConvolutionMode, int[], LayerWorkspaceMgr) - Method in class org.deeplearning4j.nn.layers.convolution.subsampling.CudnnSubsamplingHelper
-
- activate(boolean, LayerWorkspaceMgr) - Method in class org.deeplearning4j.nn.layers.convolution.subsampling.Subsampling1DLayer
-
- activate(boolean, LayerWorkspaceMgr) - Method in class org.deeplearning4j.nn.layers.convolution.subsampling.Subsampling3DLayer
-
- activate(INDArray, boolean, int[], int[], int[], PoolingType, ConvolutionMode, int[], LayerWorkspaceMgr) - Method in interface org.deeplearning4j.nn.layers.convolution.subsampling.SubsamplingHelper
-
- activate(boolean, LayerWorkspaceMgr) - Method in class org.deeplearning4j.nn.layers.convolution.subsampling.SubsamplingLayer
-
- activate(boolean, LayerWorkspaceMgr) - Method in class org.deeplearning4j.nn.layers.convolution.upsampling.Upsampling1D
-
- activate(boolean, LayerWorkspaceMgr) - Method in class org.deeplearning4j.nn.layers.convolution.upsampling.Upsampling2D
-
- activate(boolean, LayerWorkspaceMgr) - Method in class org.deeplearning4j.nn.layers.convolution.upsampling.Upsampling3D
-
- activate(boolean, LayerWorkspaceMgr) - Method in class org.deeplearning4j.nn.layers.convolution.ZeroPadding1DLayer
-
- activate(boolean, LayerWorkspaceMgr) - Method in class org.deeplearning4j.nn.layers.convolution.ZeroPadding3DLayer
-
- activate(boolean, LayerWorkspaceMgr) - Method in class org.deeplearning4j.nn.layers.convolution.ZeroPaddingLayer
-
- activate(boolean, LayerWorkspaceMgr) - Method in class org.deeplearning4j.nn.layers.DropoutLayer
-
- activate(INDArray, boolean, LayerWorkspaceMgr) - Method in class org.deeplearning4j.nn.layers.feedforward.autoencoder.AutoEncoder
-
- activate(boolean, LayerWorkspaceMgr) - Method in class org.deeplearning4j.nn.layers.feedforward.autoencoder.AutoEncoder
-
- activate(boolean, LayerWorkspaceMgr) - Method in class org.deeplearning4j.nn.layers.feedforward.embedding.EmbeddingLayer
-
- activate(boolean, LayerWorkspaceMgr) - Method in class org.deeplearning4j.nn.layers.feedforward.embedding.EmbeddingSequenceLayer
-
- activate(boolean, LayerWorkspaceMgr) - Method in class org.deeplearning4j.nn.layers.FrozenLayer
-
- activate(INDArray, boolean, LayerWorkspaceMgr) - Method in class org.deeplearning4j.nn.layers.FrozenLayer
-
- activate(boolean, LayerWorkspaceMgr) - Method in class org.deeplearning4j.nn.layers.FrozenLayerWithBackprop
-
- activate(INDArray, boolean, LayerWorkspaceMgr) - Method in class org.deeplearning4j.nn.layers.FrozenLayerWithBackprop
-
- activate(boolean, LayerWorkspaceMgr) - Method in class org.deeplearning4j.nn.layers.LossLayer
-
- activate(INDArray, boolean, LayerWorkspaceMgr) - Method in class org.deeplearning4j.nn.layers.LossLayer
-
- activate(boolean, LayerWorkspaceMgr) - Method in class org.deeplearning4j.nn.layers.normalization.BatchNormalization
-
- activate(INDArray, boolean, double, double, double, double, LayerWorkspaceMgr) - Method in class org.deeplearning4j.nn.layers.normalization.CudnnLocalResponseNormalizationHelper
-
- activate(boolean, LayerWorkspaceMgr) - Method in class org.deeplearning4j.nn.layers.normalization.LocalResponseNormalization
-
- activate(INDArray, boolean, double, double, double, double, LayerWorkspaceMgr) - Method in interface org.deeplearning4j.nn.layers.normalization.LocalResponseNormalizationHelper
-
- activate(boolean, LayerWorkspaceMgr) - Method in class org.deeplearning4j.nn.layers.objdetect.Yolo2OutputLayer
-
- activate(INDArray, INDArray) - Static method in class org.deeplearning4j.nn.layers.objdetect.YoloUtils
-
Essentially: just apply activation functions...
- activate(INDArray, INDArray, LayerWorkspaceMgr) - Static method in class org.deeplearning4j.nn.layers.objdetect.YoloUtils
-
- activate(INDArray, boolean, LayerWorkspaceMgr) - Method in class org.deeplearning4j.nn.layers.ocnn.OCNNOutputLayer
-
- activate(boolean, LayerWorkspaceMgr) - Method in class org.deeplearning4j.nn.layers.ocnn.OCNNOutputLayer
-
- activate(boolean, LayerWorkspaceMgr) - Method in class org.deeplearning4j.nn.layers.pooling.GlobalPoolingLayer
-
- activate(boolean, LayerWorkspaceMgr) - Method in class org.deeplearning4j.nn.layers.recurrent.BidirectionalLayer
-
- activate(INDArray, boolean, LayerWorkspaceMgr) - Method in class org.deeplearning4j.nn.layers.recurrent.BidirectionalLayer
-
- activate(Layer, NeuralNetConfiguration, IActivation, INDArray, INDArray, INDArray, INDArray, boolean, INDArray, INDArray, boolean, boolean, String, INDArray, boolean, LayerWorkspaceMgr) - Method in class org.deeplearning4j.nn.layers.recurrent.CudnnLSTMHelper
-
- activate(INDArray, boolean, LayerWorkspaceMgr) - Method in class org.deeplearning4j.nn.layers.recurrent.GravesBidirectionalLSTM
-
- activate(boolean, LayerWorkspaceMgr) - Method in class org.deeplearning4j.nn.layers.recurrent.GravesBidirectionalLSTM
-
- activate(INDArray, boolean, LayerWorkspaceMgr) - Method in class org.deeplearning4j.nn.layers.recurrent.GravesLSTM
-
- activate(boolean, LayerWorkspaceMgr) - Method in class org.deeplearning4j.nn.layers.recurrent.GravesLSTM
-
- activate(boolean, LayerWorkspaceMgr) - Method in class org.deeplearning4j.nn.layers.recurrent.LastTimeStepLayer
-
- activate(INDArray, boolean, LayerWorkspaceMgr) - Method in class org.deeplearning4j.nn.layers.recurrent.LastTimeStepLayer
-
- activate(INDArray, boolean, LayerWorkspaceMgr) - Method in class org.deeplearning4j.nn.layers.recurrent.LSTM
-
- activate(boolean, LayerWorkspaceMgr) - Method in class org.deeplearning4j.nn.layers.recurrent.LSTM
-
- activate(Layer, NeuralNetConfiguration, IActivation, INDArray, INDArray, INDArray, INDArray, boolean, INDArray, INDArray, boolean, boolean, String, INDArray, boolean, LayerWorkspaceMgr) - Method in interface org.deeplearning4j.nn.layers.recurrent.LSTMHelper
-
- activate(boolean, LayerWorkspaceMgr) - Method in class org.deeplearning4j.nn.layers.recurrent.MaskZeroLayer
-
- activate(INDArray, boolean, LayerWorkspaceMgr) - Method in class org.deeplearning4j.nn.layers.recurrent.MaskZeroLayer
-
- activate(boolean, LayerWorkspaceMgr) - Method in class org.deeplearning4j.nn.layers.recurrent.RnnLossLayer
-
- activate(boolean, LayerWorkspaceMgr) - Method in class org.deeplearning4j.nn.layers.recurrent.RnnOutputLayer
-
- activate(boolean, LayerWorkspaceMgr) - Method in class org.deeplearning4j.nn.layers.recurrent.SimpleRnn
-
- activate(boolean, LayerWorkspaceMgr) - Method in class org.deeplearning4j.nn.layers.samediff.SameDiffLayer
-
- activate(boolean, LayerWorkspaceMgr) - Method in class org.deeplearning4j.nn.layers.util.MaskLayer
-
- activate(boolean, LayerWorkspaceMgr) - Method in class org.deeplearning4j.nn.layers.variational.VariationalAutoencoder
-
- activate(INDArray, boolean, LayerWorkspaceMgr) - Method in class org.deeplearning4j.nn.layers.variational.VariationalAutoencoder
-
- activate(boolean, LayerWorkspaceMgr) - Method in class org.deeplearning4j.nn.layers.wrapper.BaseWrapperLayer
-
- activate(INDArray, boolean, LayerWorkspaceMgr) - Method in class org.deeplearning4j.nn.layers.wrapper.BaseWrapperLayer
-
- activate(INDArray) - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
-
- activate(Layer.TrainingMode) - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
-
- activate(INDArray, Layer.TrainingMode) - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
-
- activate(boolean, LayerWorkspaceMgr) - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
-
- activate(INDArray, boolean, LayerWorkspaceMgr) - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
-
- activateHelper(BaseLayer, NeuralNetConfiguration, IActivation, INDArray, INDArray, INDArray, INDArray, boolean, INDArray, INDArray, boolean, boolean, String, INDArray, boolean, LSTMHelper, CacheMode, LayerWorkspaceMgr) - Static method in class org.deeplearning4j.nn.layers.recurrent.LSTMHelpers
-
Returns FwdPassReturn object with activations/INDArrays.
- activateScavenger() - Method in class org.deeplearning4j.models.word2vec.wordstore.VocabularyHolder
-
This method removes low-frequency words based on their frequency change between activations.
- activateSelectedLayers(int, int, INDArray) - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
-
Calculate activation for few layers at once.
- activation(String) - Method in class org.deeplearning4j.nn.conf.layers.ActivationLayer.Builder
-
- activation(IActivation) - Method in class org.deeplearning4j.nn.conf.layers.ActivationLayer.Builder
-
- activation(Activation) - Method in class org.deeplearning4j.nn.conf.layers.ActivationLayer.Builder
-
- activation(IActivation) - Method in class org.deeplearning4j.nn.conf.layers.BaseLayer.Builder
-
Set the activation function for the layer.
- activation(Activation) - Method in class org.deeplearning4j.nn.conf.layers.BaseLayer.Builder
-
Set the activation function for the layer, from an Activation enumeration value.
- activation(IActivation) - Method in class org.deeplearning4j.nn.conf.NeuralNetConfiguration.Builder
-
Activation function / neuron non-linearity
Note: values set by this method will be applied to all applicable layers in the network, unless a different
value is explicitly set on a given layer.
- activation(Activation) - Method in class org.deeplearning4j.nn.conf.NeuralNetConfiguration.Builder
-
Activation function / neuron non-linearity
Note: values set by this method will be applied to all applicable layers in the network, unless a different
value is explicitly set on a given layer.
- activation - Variable in class org.deeplearning4j.nn.conf.ocnn.OCNNOutputLayer.Builder
-
- activation(IActivation) - Method in class org.deeplearning4j.nn.conf.ocnn.OCNNOutputLayer.Builder
-
- activation(IActivation) - Method in class org.deeplearning4j.nn.transferlearning.FineTuneConfiguration.Builder
-
Activation function / neuron non-linearity
- activation(Activation) - Method in class org.deeplearning4j.nn.transferlearning.FineTuneConfiguration.Builder
-
Activation function / neuron non-linearity
- activationFn - Variable in class org.deeplearning4j.nn.conf.layers.ActivationLayer
-
- activationFn - Variable in class org.deeplearning4j.nn.conf.layers.BaseLayer
-
- activationFn - Variable in class org.deeplearning4j.nn.conf.layers.BaseLayer.Builder
-
- activationFn - Variable in class org.deeplearning4j.nn.conf.NeuralNetConfiguration.Builder
-
- activationFn - Variable in class org.deeplearning4j.nn.transferlearning.FineTuneConfiguration
-
- activationFromPrevLayer(int, INDArray, boolean, LayerWorkspaceMgr) - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
-
- ActivationLayer - Class in org.deeplearning4j.nn.conf.layers
-
- ActivationLayer(ActivationLayer.Builder) - Constructor for class org.deeplearning4j.nn.conf.layers.ActivationLayer
-
- ActivationLayer(Activation) - Constructor for class org.deeplearning4j.nn.conf.layers.ActivationLayer
-
- ActivationLayer(IActivation) - Constructor for class org.deeplearning4j.nn.conf.layers.ActivationLayer
-
- ActivationLayer - Class in org.deeplearning4j.nn.layers
-
Activation Layer
Used to apply activation on input and corresponding derivative on epsilon.
- ActivationLayer(NeuralNetConfiguration) - Constructor for class org.deeplearning4j.nn.layers.ActivationLayer
-
- ActivationLayer(NeuralNetConfiguration, INDArray) - Constructor for class org.deeplearning4j.nn.layers.ActivationLayer
-
- ActivationLayer.Builder - Class in org.deeplearning4j.nn.conf.layers
-
- active(String) - Method in class org.ansj.dic.LearnTool
-
尝试激活，新词
- adaGrad - Variable in class org.deeplearning4j.models.embeddings.inmemory.InMemoryLookupTable
-
- adaGrad - Variable in class org.deeplearning4j.plot.BarnesHutTsne
-
- adaGrad - Variable in class org.deeplearning4j.plot.Tsne
-
- ADAGRAD - Static variable in class org.deeplearning4j.spark.models.embeddings.word2vec.Word2VecPerformerVoid
-
Deprecated.
- ADAGRAD - Static variable in class org.deeplearning4j.spark.models.embeddings.word2vec.Word2VecVariables
-
Deprecated.
- adapt2dMask(INDArray, INDArray, LayerWorkspaceMgr, ArrayType) - Static method in class org.deeplearning4j.util.ConvolutionUtils
-
- adapter - Variable in class org.deeplearning4j.spark.util.BaseDoubleFlatMapFunctionAdaptee
-
- adapter - Variable in class org.deeplearning4j.spark.util.BasePairFlatMapFunctionAdaptee
-
- add(String) - Method in class com.atilika.kuromoji.trie.Trie
-
Adds an input value to this trie
- add(String) - Method in class com.atilika.kuromoji.trie.Trie.Node
-
Add string to add to this node
- add(String, boolean) - Method in class com.atilika.kuromoji.trie.Trie.Node
-
- add(T, T) - Method in class org.deeplearning4j.eval.ConfusionMatrix
-
Increments the entry specified by actual and predicted by one.
- add(T, T, int) - Method in class org.deeplearning4j.eval.ConfusionMatrix
-
Increments the entry specified by actual and predicted by count.
- add(ConfusionMatrix<T>) - Method in class org.deeplearning4j.eval.ConfusionMatrix
-
Adds the entries from another confusion matrix to this one.
- add(CSVRecord) - Method in class org.deeplearning4j.nearestneighbor.model.BatchRecord
-
Add a record
- add(E) - Method in class org.deeplearning4j.optimize.solvers.accumulation.FancyBlockingQueue
-
- add(E) - Method in class org.deeplearning4j.parallelism.ConcurrentHashSet
-
Deprecated.
- add(T) - Method in class org.deeplearning4j.parallelism.MagicQueue
-
Deprecated.
- Add - Class in org.deeplearning4j.spark.impl.common
-
Adds 2 ndarrays
- Add() - Constructor for class org.deeplearning4j.spark.impl.common.Add
-
- add(ValidationResult) - Method in class org.deeplearning4j.spark.util.data.ValidationResult
-
- add(E) - Method in class org.deeplearning4j.util.DiskBasedQueue
-
- addAccumulator(Counter<Long>, Counter<Long>) - Method in class org.deeplearning4j.spark.models.sequencevectors.functions.ElementsFrequenciesAccumulator
-
- addAccumulator(ExtraCounter<Long>, ExtraCounter<Long>) - Method in class org.deeplearning4j.spark.models.sequencevectors.functions.ExtraElementsFrequenciesAccumulator
-
- addAccumulator(Counter<Integer>, Counter<Integer>) - Method in class org.deeplearning4j.spark.text.accumulators.MaxPerPartitionAccumulator
-
- addAccumulator(Counter<String>, Counter<String>) - Method in class org.deeplearning4j.spark.text.accumulators.WordFreqAccumulator
-
- addAll(Collection<? extends E>) - Method in class org.deeplearning4j.optimize.solvers.accumulation.FancyBlockingQueue
-
- addAll(Collection<? extends E>) - Method in class org.deeplearning4j.parallelism.ConcurrentHashSet
-
Deprecated.
- addAll(Collection<? extends T>) - Method in class org.deeplearning4j.parallelism.MagicQueue
-
Deprecated.
- addAll(Collection<? extends E>) - Method in class org.deeplearning4j.util.DiskBasedQueue
-
- addAuthHeader(HttpRequest) - Method in class org.deeplearning4j.nearestneighbor.client.NearestNeighborsClient
-
Add the specified authentication header to the specified HttpRequest
- addBiasParam(String, int[]) - Method in class org.deeplearning4j.nn.conf.layers.samediff.SDLayerParams
-
Add a bias parameter to the layer, with the specified shape.
- addBin(double, double, double) - Method in class org.deeplearning4j.ui.components.chart.ChartHistogram.Builder
-
Add a single bin
- addBos() - Method in class com.atilika.kuromoji.viterbi.ViterbiLattice
-
- addChild(Trie.Node) - Method in class com.atilika.kuromoji.trie.Trie.Node
-
Adds a new child node to this node
- addClusterInfo(String) - Method in class org.deeplearning4j.clustering.info.ClusterSetInfo
-
- addCompletionHook(long, long, long) - Method in class org.deeplearning4j.spark.parameterserver.networking.SilentTrainingDriver
-
- addComponents(Component...) - Method in class org.deeplearning4j.ui.components.decorator.DecoratorAccordion.Builder
-
Components to show internally in the accordion element
- addDistribution(int, ReconstructionDistribution) - Method in class org.deeplearning4j.nn.conf.layers.variational.CompositeReconstructionDistribution.Builder
-
Add another distribution to the composite distribution.
- addEdge(int, int, E, boolean) - Method in class org.deeplearning4j.graph.api.BaseGraph
-
- addEdge(Edge<E>) - Method in interface org.deeplearning4j.graph.api.IGraph
-
Add an edge to the graph.
- addEdge(int, int, E, boolean) - Method in interface org.deeplearning4j.graph.api.IGraph
-
Convenience method for adding an edge (directed or undirected) to graph
- addEdge(Edge<E>) - Method in class org.deeplearning4j.graph.graph.Graph
-
- addEdge(Edge<E>) - Method in class org.deeplearning4j.models.sequencevectors.graph.primitives.Graph
-
- addEdge(int, int, E, boolean) - Method in class org.deeplearning4j.models.sequencevectors.graph.primitives.Graph
-
Convenience method for adding an edge (directed or undirected) to graph
- addEdge(Edge<E>) - Method in interface org.deeplearning4j.models.sequencevectors.graph.primitives.IGraph
-
Add an edge to the graph.
- addEdge(int, int, E, boolean) - Method in interface org.deeplearning4j.models.sequencevectors.graph.primitives.IGraph
-
Convenience method for adding an edge (directed or undirected) to graph
- addElement(T) - Method in class org.deeplearning4j.models.sequencevectors.sequence.Sequence
-
Adds single element to sequence
- addElements(Collection<T>) - Method in class org.deeplearning4j.models.sequencevectors.sequence.Sequence
-
Adds collection of elements to the sequence
- addEntry(String) - Method in class com.atilika.kuromoji.dict.UserDictionary
-
- addEos() - Method in class com.atilika.kuromoji.viterbi.ViterbiLattice
-
- addFreq(int, int) - Method in class org.ansj.domain.PersonNatureAttr
-
设置
- addHook(TrainingHook) - Method in interface org.deeplearning4j.spark.api.TrainingMaster
-
Add a hook for the master for pre and post training
- addHook(TrainingHook) - Method in interface org.deeplearning4j.spark.api.TrainingWorker
-
Add a training hook to be used
during training of the worker
- addHook(TrainingHook) - Method in class org.deeplearning4j.spark.impl.paramavg.ParameterAveragingTrainingMaster
-
Add a hook for the master for pre and post training
- addHook(TrainingHook) - Method in class org.deeplearning4j.spark.impl.paramavg.ParameterAveragingTrainingWorker
-
Add a training hook to be used
during training of the worker
- addHook(TrainingHook) - Method in class org.deeplearning4j.spark.parameterserver.training.SharedTrainingMaster
-
- addHook(TrainingHook) - Method in class org.deeplearning4j.spark.parameterserver.training.SharedTrainingWorker
-
- addInPlace(Counter<Long>, Counter<Long>) - Method in class org.deeplearning4j.spark.models.sequencevectors.functions.ElementsFrequenciesAccumulator
-
- addInPlace(ExtraCounter<Long>, ExtraCounter<Long>) - Method in class org.deeplearning4j.spark.models.sequencevectors.functions.ExtraElementsFrequenciesAccumulator
-
- addInPlace(Counter<Integer>, Counter<Integer>) - Method in class org.deeplearning4j.spark.text.accumulators.MaxPerPartitionAccumulator
-
- addInPlace(Counter<String>, Counter<String>) - Method in class org.deeplearning4j.spark.text.accumulators.WordFreqAccumulator
-
- addInput(String) - Method in class org.deeplearning4j.datasets.datavec.RecordReaderMultiDataSetIterator.Builder
-
Set as an input, the entire contents (all columns) of the RecordReader or SequenceRecordReader
- addInput(String, int, int) - Method in class org.deeplearning4j.datasets.datavec.RecordReaderMultiDataSetIterator.Builder
-
Set as an input, a subset of the specified RecordReader or SequenceRecordReader
- addInput(INDArray...) - Method in interface org.deeplearning4j.parallelism.inference.InferenceObservable
-
- addInput(INDArray[], INDArray[]) - Method in interface org.deeplearning4j.parallelism.inference.InferenceObservable
-
- addInput(INDArray...) - Method in class org.deeplearning4j.parallelism.inference.observers.BasicInferenceObservable
-
- addInput(INDArray[], INDArray[]) - Method in class org.deeplearning4j.parallelism.inference.observers.BasicInferenceObservable
-
- addInput(INDArray[], INDArray[]) - Method in class org.deeplearning4j.parallelism.inference.observers.BatchedInferenceObservable
-
- addInputOneHot(String, int, int) - Method in class org.deeplearning4j.datasets.datavec.RecordReaderMultiDataSetIterator.Builder
-
Add as an input a single column from the specified RecordReader / SequenceRecordReader
The assumption is that the specified column contains integer values in range 0..numClasses-1;
this integer will be converted to a one-hot representation
- addInputs(String...) - Method in class org.deeplearning4j.nn.conf.ComputationGraphConfiguration.GraphBuilder
-
Specify the inputs to the network, and their associated labels.
- addInputs(Collection<String>) - Method in class org.deeplearning4j.nn.conf.ComputationGraphConfiguration.GraphBuilder
-
Specify the inputs to the network, and their associated labels.
- addInputs(String...) - Method in class org.deeplearning4j.nn.transferlearning.TransferLearning.GraphBuilder
-
- addKeyFile(String) - Method in class org.deeplearning4j.aws.ec2.provision.HostProvisioner
-
- addLabel(String) - Method in class org.deeplearning4j.text.documentiterator.LabelledDocument
-
- addLabelForDoc(int, T) - Method in interface org.deeplearning4j.text.invertedindex.InvertedIndex
-
Add word to a document
- addLabelForDoc(int, String) - Method in interface org.deeplearning4j.text.invertedindex.InvertedIndex
-
Adds words to the given document
- addLabelsForDoc(int, List<T>) - Method in interface org.deeplearning4j.text.invertedindex.InvertedIndex
-
Add word to a document
- addLabelsForDoc(int, Collection<String>) - Method in interface org.deeplearning4j.text.invertedindex.InvertedIndex
-
Adds words to the given document
- addLane(String, List<ChartTimeline.TimelineEntry>) - Method in class org.deeplearning4j.ui.components.chart.ChartTimeline.Builder
-
- addLayer(String, Layer, String...) - Method in class org.deeplearning4j.nn.conf.ComputationGraphConfiguration.GraphBuilder
-
Add a layer, with no
InputPreProcessor, with the specified name and specified inputs.
- addLayer(String, Layer, InputPreProcessor, String...) - Method in class org.deeplearning4j.nn.conf.ComputationGraphConfiguration.GraphBuilder
-
- addLayer(Layer) - Method in class org.deeplearning4j.nn.transferlearning.TransferLearning.Builder
-
Add layers to the net
Required if layers are removed.
- addLayer(String, Layer, String...) - Method in class org.deeplearning4j.nn.transferlearning.TransferLearning.GraphBuilder
-
Add a layer of the specified configuration to the computation graph
- addLayer(String, Layer, InputPreProcessor, String...) - Method in class org.deeplearning4j.nn.transferlearning.TransferLearning.GraphBuilder
-
Add a layer with a specified preprocessor
- addLayers(ComputationGraphConfiguration.GraphBuilder, int, int, int, int, int) - Static method in class org.deeplearning4j.zoo.model.helper.DarknetHelper
-
- addLayers(ComputationGraphConfiguration.GraphBuilder, int, int, int, int, int, int) - Static method in class org.deeplearning4j.zoo.model.helper.DarknetHelper
-
- addLayers(ComputationGraphConfiguration.GraphBuilder, int, String, int, int, int, int, int) - Static method in class org.deeplearning4j.zoo.model.helper.DarknetHelper
-
- addListeners(TrainingListener...) - Method in interface org.deeplearning4j.nn.api.Model
-
This method ADDS additional TrainingListener to existing listeners
- addListeners(TrainingListener...) - Method in class org.deeplearning4j.nn.graph.ComputationGraph
-
This method ADDS additional TrainingListener to existing listeners
- addListeners(TrainingListener...) - Method in class org.deeplearning4j.nn.layers.AbstractLayer
-
This method ADDS additional TrainingListener to existing listeners
- addListeners(TrainingListener...) - Method in class org.deeplearning4j.nn.layers.recurrent.BidirectionalLayer
-
- addListeners(TrainingListener...) - Method in class org.deeplearning4j.nn.layers.variational.VariationalAutoencoder
-
This method ADDS additional TrainingListener to existing listeners
- addListeners(TrainingListener...) - Method in class org.deeplearning4j.nn.layers.wrapper.BaseWrapperLayer
-
- addListeners(TrainingListener...) - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
-
This method ADDS additional TrainingListener to existing listeners
- addListeners(TrainingListener...) - Method in class org.deeplearning4j.plot.BarnesHutTsne
-
- addMapping(int, int) - Method in class com.atilika.kuromoji.compile.TokenInfoDictionaryCompilerBase
-
- addMapping(int, int) - Method in class com.atilika.kuromoji.compile.WordIdMapCompiler
-
- addNewClusterWithCenter(Point) - Method in class org.deeplearning4j.clustering.cluster.ClusterSet
-
- addNodeAtIndex(int, INDArray) - Method in class org.deeplearning4j.clustering.randomprojection.RPTree
-
- addNormalizerToModel(File, Normalizer<?>) - Static method in class org.deeplearning4j.util.ModelSerializer
-
This method appends normalizer to a given persisted model.
- addObjectToFile(File, String, Object) - Static method in class org.deeplearning4j.util.ModelSerializer
-
Add an object to the (already existing) model file using Java Object Serialization.
- addObserver(Observer) - Method in interface org.deeplearning4j.parallelism.inference.InferenceObservable
-
- addOtherTrainingStats(SparkTrainingStats) - Method in class org.deeplearning4j.spark.api.stats.CommonSparkTrainingStats
-
- addOtherTrainingStats(SparkTrainingStats) - Method in interface org.deeplearning4j.spark.api.stats.SparkTrainingStats
-
Combine the two training stats instances.
- addOtherTrainingStats(SparkTrainingStats) - Method in class org.deeplearning4j.spark.impl.paramavg.stats.ParameterAveragingTrainingMasterStats
-
- addOtherTrainingStats(SparkTrainingStats) - Method in class org.deeplearning4j.spark.impl.paramavg.stats.ParameterAveragingTrainingWorkerStats
-
- addOutput(String) - Method in class org.deeplearning4j.datasets.datavec.RecordReaderMultiDataSetIterator.Builder
-
Set as an output, the entire contents (all columns) of the RecordReader or SequenceRecordReader
- addOutput(String, int, int) - Method in class org.deeplearning4j.datasets.datavec.RecordReaderMultiDataSetIterator.Builder
-
Add an output, with a subset of the columns from the named RecordReader or SequenceRecordReader
- addOutputOneHot(String, int, int) - Method in class org.deeplearning4j.datasets.datavec.RecordReaderMultiDataSetIterator.Builder
-
An an output, where the output is taken from a single column from the specified RecordReader / SequenceRecordReader
The assumption is that the specified column contains integer values in range 0..numClasses-1;
this integer will be converted to a one-hot representation (usually for classification)
- addPoint(Point) - Method in class org.deeplearning4j.clustering.cluster.Cluster
-
Add a point to the cluster
- addPoint(Point, boolean) - Method in class org.deeplearning4j.clustering.cluster.Cluster
-
Add a point to the cluster
- addPreProcessor(MultiDataSetPreProcessor) - Method in class org.deeplearning4j.datasets.iterator.CombinedMultiDataSetPreProcessor.Builder
-
- addPreProcessor(int, MultiDataSetPreProcessor) - Method in class org.deeplearning4j.datasets.iterator.CombinedMultiDataSetPreProcessor.Builder
-
Inserts the specified preprocessor at the specified position to the list of preprocessors to be applied
- addPreProcessor(DataSetPreProcessor) - Method in class org.deeplearning4j.datasets.iterator.CombinedPreProcessor.Builder
-
- addPreProcessor(int, DataSetPreProcessor) - Method in class org.deeplearning4j.datasets.iterator.CombinedPreProcessor.Builder
-
- addPreProcessors(InputType...) - Method in class org.deeplearning4j.nn.conf.ComputationGraphConfiguration
-
Add preprocessors automatically, given the specified types of inputs for the network.
- addRandomHyperPlane() - Method in class org.deeplearning4j.clustering.randomprojection.RPHyperPlanes
-
Add a new random element to the hyper plane.
- addReader(String, RecordReader) - Method in class org.deeplearning4j.datasets.datavec.RecordReaderMultiDataSetIterator.Builder
-
Add a RecordReader for use in .addInput(...) or .addOutput(...)
- addSentenceIterator(SentenceIterator) - Method in class org.deeplearning4j.text.sentenceiterator.AggregatingSentenceIterator.Builder
-
- addSentenceIterators(Collection<SentenceIterator>) - Method in class org.deeplearning4j.text.sentenceiterator.AggregatingSentenceIterator.Builder
-
- addSentencePreProcessor(SentencePreProcessor) - Method in class org.deeplearning4j.text.sentenceiterator.AggregatingSentenceIterator.Builder
-
- addSequenceLabel(T) - Method in class org.deeplearning4j.models.sequencevectors.sequence.Sequence
-
Adds sequence label.
- addSequenceReader(String, SequenceRecordReader) - Method in class org.deeplearning4j.datasets.datavec.RecordReaderMultiDataSetIterator.Builder
-
Add a SequenceRecordReader for use in .addInput(...) or .addOutput(...)
- addSeries(String, double[], double[]) - Method in class org.deeplearning4j.ui.components.chart.ChartLine.Builder
-
- addSeries(String, double[], double[]) - Method in class org.deeplearning4j.ui.components.chart.ChartScatter.Builder
-
- addSeries(String, double[]) - Method in class org.deeplearning4j.ui.components.chart.ChartStackedArea.Builder
-
Add a single series.
- addSource(SequenceIterator<T>, int) - Method in class org.deeplearning4j.models.word2vec.wordstore.VocabConstructor.Builder
-
Adds SequenceIterator for vocabulary construction.
- addSourceFolder(File) - Method in class org.deeplearning4j.text.documentiterator.FileLabelAwareIterator.Builder
-
Root folder for labels -> documents.
- addSourceFolder(File) - Method in class org.deeplearning4j.text.documentiterator.FilenamesLabelAwareIterator.Builder
-
Root folder for labels -> documents.
- addSourceIterator(DataSetIterator) - Method in class org.deeplearning4j.datasets.iterator.parallel.JointParallelDataSetIterator.Builder
-
- addTerm(NewWord) - Method in class org.ansj.dic.LearnTool
-
增加一个新词到树中
- addTerm(Term) - Method in class org.ansj.util.Graph
-
增加一个词语到图中
- addToConfusion(Integer, Integer) - Method in class org.deeplearning4j.eval.Evaluation
-
Adds to the confusion matrix
- addToken(T) - Method in class org.deeplearning4j.models.word2vec.wordstore.inmemory.AbstractCache
-
This method adds specified SequenceElement to vocabulary
- addToken(VocabWord) - Method in class org.deeplearning4j.models.word2vec.wordstore.inmemory.InMemoryLookupCache
-
Deprecated.
- addToken(T) - Method in interface org.deeplearning4j.models.word2vec.wordstore.VocabCache
-
Adds a token
to the cache
- addValue(String, double) - Method in class org.deeplearning4j.ui.components.chart.ChartHorizontalBar.Builder
-
- addValues(List<String>, double[]) - Method in class org.deeplearning4j.ui.components.chart.ChartHorizontalBar.Builder
-
- addValues(List<String>, float[]) - Method in class org.deeplearning4j.ui.components.chart.ChartHorizontalBar.Builder
-
- addVariable(String) - Method in class org.deeplearning4j.nn.conf.NeuralNetConfiguration
-
- addVertex(Vertex<V>, Edge<E>) - Method in class org.deeplearning4j.models.sequencevectors.graph.primitives.Graph
-
- addVertex(Vertex<V>, Collection<Edge<E>>) - Method in class org.deeplearning4j.models.sequencevectors.graph.primitives.Graph
-
- addVertex(String, GraphVertex, String...) - Method in class org.deeplearning4j.nn.conf.ComputationGraphConfiguration.GraphBuilder
-
- addVertex(String, GraphVertex, String...) - Method in class org.deeplearning4j.nn.transferlearning.TransferLearning.GraphBuilder
-
Add a vertex of the given configuration to the computation graph
- addWeightParam(String, int...) - Method in class org.deeplearning4j.nn.conf.layers.samediff.SDLayerParams
-
Add a weight parameter to the layer, with the specified shape.
- addWord(String) - Method in class org.deeplearning4j.models.word2vec.wordstore.VocabularyHolder
-
Adds new word to vocabulary
- addWord(VocabularyWord) - Method in class org.deeplearning4j.models.word2vec.wordstore.VocabularyHolder
-
- addWordsToDoc(int, List<T>) - Method in interface org.deeplearning4j.text.invertedindex.InvertedIndex
-
Adds words to the given document
- addWordsToDoc(int, List<T>, String) - Method in interface org.deeplearning4j.text.invertedindex.InvertedIndex
-
Adds words to the given document
- addWordsToDoc(int, List<T>, T) - Method in interface org.deeplearning4j.text.invertedindex.InvertedIndex
-
Adds words to the given document
- addWordsToDoc(int, List<T>, Collection<String>) - Method in interface org.deeplearning4j.text.invertedindex.InvertedIndex
-
Adds words to the given document
- addWordsToDocVocabWord(int, List<T>, Collection<T>) - Method in interface org.deeplearning4j.text.invertedindex.InvertedIndex
-
Adds words to the given document
- addWordToDoc(int, T) - Method in interface org.deeplearning4j.text.invertedindex.InvertedIndex
-
Add word to a document
- addWordToIndex(int, String) - Method in class org.deeplearning4j.models.word2vec.wordstore.inmemory.AbstractCache
-
This method allows to insert specified label to specified Huffman tree position.
- addWordToIndex(int, long) - Method in class org.deeplearning4j.models.word2vec.wordstore.inmemory.AbstractCache
-
- addWordToIndex(int, String) - Method in class org.deeplearning4j.models.word2vec.wordstore.inmemory.InMemoryLookupCache
-
Deprecated.
- addWordToIndex(int, long) - Method in class org.deeplearning4j.models.word2vec.wordstore.inmemory.InMemoryLookupCache
-
Deprecated.
- addWordToIndex(int, String) - Method in interface org.deeplearning4j.models.word2vec.wordstore.VocabCache
-
- addWordToIndex(int, long) - Method in interface org.deeplearning4j.models.word2vec.wordstore.VocabCache
-
- addWorkerStats(SparkTrainingStats) - Method in class org.deeplearning4j.spark.impl.paramavg.stats.ParameterAveragingTrainingMasterStats.ParameterAveragingTrainingMasterStatsHelper
-
- adjustBlock(ComputationGraphConfiguration.GraphBuilder, int, String, String) - Static method in class org.deeplearning4j.zoo.model.helper.NASNetHelper
-
- adjustBlock(ComputationGraphConfiguration.GraphBuilder, int, String, String, String) - Static method in class org.deeplearning4j.zoo.model.helper.NASNetHelper
-
- adjustedrSquared(double, int, int) - Static method in class org.deeplearning4j.clustering.util.MathUtils
-
This calculates the adjusted r^2 including degrees of freedom.
- affinityId - Variable in class org.deeplearning4j.models.word2vec.VocabWord
-
- AggregatingSentenceIterator - Class in org.deeplearning4j.text.sentenceiterator
-
This is simple wrapper suited for aggregation of few SentenceIterators into single flow.
- AggregatingSentenceIterator.Builder - Class in org.deeplearning4j.text.sentenceiterator
-
- aggregationDepth - Variable in class org.deeplearning4j.spark.impl.paramavg.ParameterAveragingTrainingMaster
-
- aggregationDepth - Variable in class org.deeplearning4j.spark.impl.paramavg.ParameterAveragingTrainingMaster.Builder
-
- aggregationDepth(int) - Method in class org.deeplearning4j.spark.impl.paramavg.ParameterAveragingTrainingMaster.Builder
-
The number of levels in the aggregation tree for parameter synchronization.
- aggregationFinished(VoidAggregation) - Method in class org.deeplearning4j.spark.parameterserver.networking.SilentTrainingDriver
-
- AgronaPersistable - Interface in org.deeplearning4j.ui.storage
-
Created by Alex on 07/10/2016.
- AlexNet - Class in org.deeplearning4j.zoo.model
-
AlexNet
Dl4j's AlexNet model interpretation based on the original paper ImageNet Classification with Deep Convolutional Neural Networks
and the imagenetExample code referenced.
- ALF - Variable in class org.deeplearning4j.optimize.solvers.BackTrackLineSearch
-
- allDepleted - Variable in class org.deeplearning4j.datasets.iterator.parallel.BaseParallelDataSetIterator
-
- allDocs() - Method in interface org.deeplearning4j.text.invertedindex.InvertedIndex
-
Returns a list of all documents
- allFalse() - Method in class org.deeplearning4j.datasets.iterator.parallel.MultiBoolean
-
This method returns true if ALL states are false.
- allFeatureCount - Variable in class org.ansj.app.crf.Model
-
- allFreq - Variable in class org.ansj.domain.PersonNatureAttr
-
- allFreq - Variable in class org.ansj.domain.TermNatures
-
所有的词频
- allFrequency - Variable in class org.ansj.domain.Nature
-
- allLabels() - Method in interface org.deeplearning4j.iterator.LabeledSentenceProvider
-
Return the list of labels - this also defines the class/integer label assignment order
- allLabels() - Method in class org.deeplearning4j.iterator.provider.CollectionLabeledSentenceProvider
-
- allLabels() - Method in class org.deeplearning4j.iterator.provider.FileLabeledSentenceProvider
-
- allLabels() - Method in class org.deeplearning4j.iterator.provider.LabelAwareConverter
-
- allowDisconnected - Variable in class org.deeplearning4j.nn.conf.ComputationGraphConfiguration.GraphBuilder
-
- allowDisconnected(boolean) - Method in class org.deeplearning4j.nn.conf.ComputationGraphConfiguration.GraphBuilder
-
Used only during validation after building.
If true: don't throw an exception on configurations containing vertices that are 'disconnected'.
- allowEmptyClusters - Variable in class org.deeplearning4j.clustering.strategy.BaseClusteringStrategy
-
- allowMultithreading - Variable in class org.deeplearning4j.models.sequencevectors.transformers.impl.iterables.BasicTransformerIterator
-
- allowMultithreading - Variable in class org.deeplearning4j.models.sequencevectors.transformers.impl.SentenceTransformer
-
- allowMultithreading - Variable in class org.deeplearning4j.models.sequencevectors.transformers.impl.SentenceTransformer.Builder
-
- allowMultithreading(boolean) - Method in class org.deeplearning4j.models.sequencevectors.transformers.impl.SentenceTransformer.Builder
-
This method enables/disables parallel processing over sentences
- allowNoOutput - Variable in class org.deeplearning4j.nn.conf.ComputationGraphConfiguration.GraphBuilder
-
- allowNoOutput(boolean) - Method in class org.deeplearning4j.nn.conf.ComputationGraphConfiguration.GraphBuilder
-
Used only during validation after building.
If true: don't throw an exception on configurations without any outputs.
- allowParallelTokenization(boolean) - Method in class org.deeplearning4j.bagofwords.vectorizer.BagOfWordsVectorizer.Builder
-
- allowParallelTokenization(boolean) - Method in class org.deeplearning4j.bagofwords.vectorizer.TfidfVectorizer.Builder
-
- allowParallelTokenization(boolean) - Method in class org.deeplearning4j.models.paragraphvectors.ParagraphVectors.Builder
-
This method enables/disables parallel tokenization.
- allowParallelTokenization - Variable in class org.deeplearning4j.models.word2vec.Word2Vec.Builder
-
- allowParallelTokenization(boolean) - Method in class org.deeplearning4j.models.word2vec.Word2Vec.Builder
-
This method enables/disables parallel tokenization.
- allowParallelTokenization(boolean) - Method in class org.deeplearning4j.models.word2vec.wordstore.VocabConstructor.Builder
-
- allParamConstraints - Variable in class org.deeplearning4j.nn.conf.layers.Layer.Builder
-
- allParamConstraints - Variable in class org.deeplearning4j.nn.conf.NeuralNetConfiguration.Builder
-
- allRunning() - Method in class org.deeplearning4j.aws.ec2.Ec2BoxCreator
-
- allTrue() - Method in class org.deeplearning4j.datasets.iterator.parallel.MultiBoolean
-
This method returns true if ALL states are true.
- allWords() - Method in interface org.ansj.splitWord.GetWords
-
全文全词全匹配
- allWords() - Method in class org.ansj.splitWord.impl.GetWordsImpl
-
- alpha - Variable in class org.deeplearning4j.models.embeddings.learning.impl.elements.GloVe
-
- alpha - Variable in class org.deeplearning4j.models.embeddings.learning.impl.elements.GloVe.Builder
-
- alpha(double) - Method in class org.deeplearning4j.models.embeddings.learning.impl.elements.GloVe.Builder
-
Parameter in exponent of weighting function; default 0.75
- alpha - Variable in class org.deeplearning4j.models.glove.Glove.Builder
-
- alpha(double) - Method in class org.deeplearning4j.models.glove.Glove.Builder
-
Parameter in exponent of weighting function; default 0.75
- alpha - Variable in class org.deeplearning4j.models.sequencevectors.graph.walkers.impl.RandomWalker
-
- alpha - Variable in class org.deeplearning4j.models.sequencevectors.graph.walkers.impl.RandomWalker.Builder
-
- alpha - Variable in class org.deeplearning4j.nn.conf.layers.CenterLossOutputLayer
-
- alpha - Variable in class org.deeplearning4j.nn.conf.layers.CenterLossOutputLayer.Builder
-
- alpha(double) - Method in class org.deeplearning4j.nn.conf.layers.CenterLossOutputLayer.Builder
-
- alpha - Variable in class org.deeplearning4j.nn.conf.layers.LocalResponseNormalization
-
- alpha(double) - Method in class org.deeplearning4j.nn.conf.layers.LocalResponseNormalization.Builder
-
LRN scaling constant alpha.
- alpha - Variable in class org.deeplearning4j.nn.layers.BaseCudnnHelper
-
- ALPHA - Static variable in class org.deeplearning4j.spark.models.embeddings.glove.GlovePerformer
-
- ALPHA - Static variable in class org.deeplearning4j.spark.models.embeddings.word2vec.Word2VecPerformerVoid
-
Deprecated.
- ALPHA - Static variable in class org.deeplearning4j.spark.models.embeddings.word2vec.Word2VecVariables
-
Deprecated.
- AlphaDropout - Class in org.deeplearning4j.nn.conf.dropout
-
AlphaDropout is a dropout technique proposed by Klaumbauer et al.
- AlphaDropout(double) - Constructor for class org.deeplearning4j.nn.conf.dropout.AlphaDropout
-
- AlphaDropout(ISchedule) - Constructor for class org.deeplearning4j.nn.conf.dropout.AlphaDropout
-
- AlphaDropout(double, ISchedule, double, double) - Constructor for class org.deeplearning4j.nn.conf.dropout.AlphaDropout
-
- AmbiguityLibrary - Class in org.ansj.library
-
- AmbiguityLibrary() - Constructor for class org.ansj.library.AmbiguityLibrary
-
- Analysis - Class in org.ansj.splitWord
-
基本分词+人名识别
- Analysis() - Constructor for class org.ansj.splitWord.Analysis
-
- Analysis.Merger - Class in org.ansj.splitWord
-
- analyzeTokenInfo(InputStream) - Method in class com.atilika.kuromoji.compile.TokenInfoDictionaryCompilerBase
-
- ancestor(int, Tree) - Method in class org.deeplearning4j.nn.layers.feedforward.autoencoder.recursive.Tree
-
Returns the ancestor of the given tree
- AnsjItem - Class in org.ansj.domain
-
- AnsjItem() - Constructor for class org.ansj.domain.AnsjItem
-
- AnsjReader - Class in org.ansj.util
-
我又剽窃了下jdk...职业嫖客 为了效率这个流的操作是不支持多线程的,要么就是长时间不写这种东西了。发现好费劲啊 这个reader的特点。。只会输入
句子不会输出\r\n .会有一个start来记录当前返回字符串。起始偏移量
- AnsjReader(Reader, int) - Constructor for class org.ansj.util.AnsjReader
-
Creates a buffering character-input stream that uses an input buffer of
the specified size.
- AnsjReader(Reader) - Constructor for class org.ansj.util.AnsjReader
-
Creates a buffering character-input stream that uses a default-sized
input buffer.
- append(String, String[]) - Static method in class org.ansj.library.SynonymsLibrary
-
合并更新同义词 覆盖更新同义词 [中国, 中华, 我国] -> append([中国,华夏]) -> [中国, 中华, 我国 , 华夏]
- appendGraph(ComputationGraphConfiguration.GraphBuilder, String, int, int[], int[], int[], int[], SubsamplingLayer.PoolingType, Activation, String) - Static method in class org.deeplearning4j.zoo.model.helper.FaceNetHelper
-
- appendGraph(ComputationGraphConfiguration.GraphBuilder, String, int, int[], int[], int[], int[], SubsamplingLayer.PoolingType, int, Activation, String) - Static method in class org.deeplearning4j.zoo.model.helper.FaceNetHelper
-
- appendGraph(ComputationGraphConfiguration.GraphBuilder, String, int, int[], int[], int[], int[], SubsamplingLayer.PoolingType, int, int, Activation, String) - Static method in class org.deeplearning4j.zoo.model.helper.FaceNetHelper
-
- appendGraph(ComputationGraphConfiguration.GraphBuilder, String, int, int[], int[], int[], int[], SubsamplingLayer.PoolingType, int, int, int, Activation, String) - Static method in class org.deeplearning4j.zoo.model.helper.FaceNetHelper
-
Appends inception layer configurations a GraphBuilder object, based on the concept of
Inception via the GoogleLeNet paper: https://arxiv.org/abs/1409.4842
- appendTo(StringBuilder) - Method in class org.deeplearning4j.ui.stats.sbe.GroupSizeEncodingDecoder
-
- appendTo(StringBuilder) - Method in class org.deeplearning4j.ui.stats.sbe.GroupSizeEncodingEncoder
-
- appendTo(StringBuilder) - Method in class org.deeplearning4j.ui.stats.sbe.InitFieldsPresentDecoder
-
- appendTo(StringBuilder) - Method in class org.deeplearning4j.ui.stats.sbe.StaticInfoDecoder
-
- appendTo(StringBuilder) - Method in class org.deeplearning4j.ui.stats.sbe.StaticInfoDecoder.HwDeviceInfoGroupDecoder
-
- appendTo(StringBuilder) - Method in class org.deeplearning4j.ui.stats.sbe.StaticInfoDecoder.ModelParamNamesDecoder
-
- appendTo(StringBuilder) - Method in class org.deeplearning4j.ui.stats.sbe.StaticInfoDecoder.SwEnvironmentInfoDecoder
-
- appendTo(StringBuilder) - Method in class org.deeplearning4j.ui.stats.sbe.StaticInfoEncoder
-
- appendTo(StringBuilder) - Method in class org.deeplearning4j.ui.stats.sbe.StorageMetaDataDecoder
-
- appendTo(StringBuilder) - Method in class org.deeplearning4j.ui.stats.sbe.StorageMetaDataDecoder.ExtraMetaDataBytesDecoder
-
- appendTo(StringBuilder) - Method in class org.deeplearning4j.ui.stats.sbe.StorageMetaDataEncoder
-
- appendTo(StringBuilder) - Method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder
-
- appendTo(StringBuilder) - Method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder.DataSetMetaDataBytesDecoder
-
- appendTo(StringBuilder) - Method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder.DataSetMetaDataBytesDecoder.MetaDataBytesDecoder
-
- appendTo(StringBuilder) - Method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder.GcStatsDecoder
-
- appendTo(StringBuilder) - Method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder.LayerNamesDecoder
-
- appendTo(StringBuilder) - Method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder.MemoryUseDecoder
-
- appendTo(StringBuilder) - Method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder.ParamNamesDecoder
-
- appendTo(StringBuilder) - Method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder.PerformanceDecoder
-
- appendTo(StringBuilder) - Method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder.PerParameterStatsDecoder
-
- appendTo(StringBuilder) - Method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder.PerParameterStatsDecoder.HistogramsDecoder
-
- appendTo(StringBuilder) - Method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder.PerParameterStatsDecoder.HistogramsDecoder.HistogramCountsDecoder
-
- appendTo(StringBuilder) - Method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder.PerParameterStatsDecoder.SummaryStatDecoder
-
- appendTo(StringBuilder) - Method in class org.deeplearning4j.ui.stats.sbe.UpdateEncoder
-
- appendTo(StringBuilder) - Method in class org.deeplearning4j.ui.stats.sbe.UpdateFieldsPresentDecoder
-
- appendTo(StringBuilder) - Method in class org.deeplearning4j.ui.stats.sbe.VarDataUTF8Decoder
-
- appendTo(StringBuilder) - Method in class org.deeplearning4j.ui.stats.sbe.VarDataUTF8Encoder
-
- appliedConfiguration - Variable in class org.deeplearning4j.optimize.solvers.accumulation.EncodedGradientsAccumulator
-
- appliedNeuralNetConfiguration(NeuralNetConfiguration) - Method in class org.deeplearning4j.nn.transferlearning.FineTuneConfiguration
-
- appliedNeuralNetConfigurationBuilder() - Method in class org.deeplearning4j.nn.transferlearning.FineTuneConfiguration
-
- apply(INDArray) - Method in class org.deeplearning4j.nn.conf.constraint.BaseConstraint
-
- apply(INDArray) - Method in class org.deeplearning4j.nn.conf.constraint.MaxNormConstraint
-
- apply(INDArray) - Method in class org.deeplearning4j.nn.conf.constraint.MinMaxNormConstraint
-
- apply(INDArray) - Method in class org.deeplearning4j.nn.conf.constraint.NonNegativeConstraint
-
- apply(INDArray) - Method in class org.deeplearning4j.nn.conf.constraint.UnitNormConstraint
-
- apply(GloveWeightLookupTable) - Method in class org.deeplearning4j.spark.models.embeddings.glove.GloveChange
-
Apply the changes to the table
- apply(InMemoryLookupTable) - Method in class org.deeplearning4j.spark.models.embeddings.word2vec.Word2VecChange
-
Deprecated.
Take the changes and apply them
to the given table
- apply(String) - Method in class org.deeplearning4j.ui.play.staticroutes.Assets
-
- apply(String) - Method in class org.deeplearning4j.ui.play.staticroutes.I18NRoute
-
- applyClusteringStrategy() - Method in class org.deeplearning4j.clustering.algorithm.BaseClusteringAlgorithm
-
- applyConstraint(Layer, int, int) - Method in interface org.deeplearning4j.nn.api.layers.LayerConstraint
-
Apply a given constraint to a layer at each iteration
in the provided epoch, after parameters have been updated.
- applyConstraint(Layer, int, int) - Method in class org.deeplearning4j.nn.conf.constraint.BaseConstraint
-
- applyConstraints(int, int) - Method in interface org.deeplearning4j.nn.api.Model
-
Apply any constraints to the model
- applyConstraints(int, int) - Method in class org.deeplearning4j.nn.graph.ComputationGraph
-
- applyConstraints(int, int) - Method in class org.deeplearning4j.nn.layers.AbstractLayer
-
- applyConstraints(int, int) - Method in class org.deeplearning4j.nn.layers.FrozenLayer
-
- applyConstraints(int, int) - Method in class org.deeplearning4j.nn.layers.FrozenLayerWithBackprop
-
- applyConstraints(int, int) - Method in class org.deeplearning4j.nn.layers.recurrent.BidirectionalLayer
-
- applyConstraints(int, int) - Method in class org.deeplearning4j.nn.layers.variational.VariationalAutoencoder
-
- applyConstraints(int, int) - Method in class org.deeplearning4j.nn.layers.wrapper.BaseWrapperLayer
-
- applyConstraints(int, int) - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
-
- applyConstraints(Model) - Static method in class org.deeplearning4j.optimize.solvers.BaseOptimizer
-
- applyConstraints(int, int) - Method in class org.deeplearning4j.plot.BarnesHutTsne
-
- applyDropout(INDArray, int, int, boolean) - Method in class org.deeplearning4j.nn.conf.dropout.AlphaDropout
-
- applyDropout(INDArray, int, int, boolean) - Method in class org.deeplearning4j.nn.conf.dropout.Dropout
-
- applyDropout(INDArray, int, int, boolean) - Method in class org.deeplearning4j.nn.conf.dropout.GaussianDropout
-
- applyDropout(INDArray, int, int, boolean) - Method in class org.deeplearning4j.nn.conf.dropout.GaussianNoise
-
- applyDropout(INDArray, int, int, boolean) - Method in interface org.deeplearning4j.nn.conf.dropout.IDropout
-
- applyDropout(INDArray, int, int, boolean) - Method in class org.deeplearning4j.nn.conf.dropout.SpatialDropout
-
- applyDropOutIfNecessary(boolean, LayerWorkspaceMgr) - Method in class org.deeplearning4j.nn.layers.AbstractLayer
-
- applyDropOutIfNecessary(boolean, LayerWorkspaceMgr) - Method in class org.deeplearning4j.nn.layers.feedforward.embedding.EmbeddingLayer
-
- applyDropOutIfNecessary(boolean, LayerWorkspaceMgr) - Method in class org.deeplearning4j.nn.layers.feedforward.embedding.EmbeddingSequenceLayer
-
- applyGlobalConfig(NeuralNetConfiguration.Builder) - Method in class org.deeplearning4j.nn.conf.layers.samediff.AbstractSameDiffLayer
-
- applyGlobalConfigToLayer(NeuralNetConfiguration.Builder) - Method in class org.deeplearning4j.nn.conf.layers.samediff.AbstractSameDiffLayer
-
Apply the global configuration (weight init, activation function, etc) to this layer
- applyGlobalConfigToLayer(NeuralNetConfiguration.Builder) - Method in class org.deeplearning4j.nn.conf.layers.samediff.BaseSameDiffLayer
-
- applyIndexes(VocabCache<? extends SequenceElement>) - Method in class org.deeplearning4j.models.word2vec.Huffman
-
This method updates VocabCache and all it's elements with Huffman indexes
Please note: it should be the same VocabCache as was used for Huffman tree initialization
- applyMask(INDArray) - Method in class org.deeplearning4j.nn.layers.AbstractLayer
-
- applyMask(INDArray) - Method in class org.deeplearning4j.nn.layers.BaseOutputLayer
-
- applyOptimization(OptimisationStrategy, ClusterSet, ClusterSetInfo, ExecutorService) - Static method in class org.deeplearning4j.clustering.cluster.ClusterUtils
-
- applyPreprocessor(T) - Method in class org.deeplearning4j.datasets.iterator.file.BaseFileIterator
-
- applyPreprocessor(DataSet) - Method in class org.deeplearning4j.datasets.iterator.file.FileDataSetIterator
-
- applyPreprocessor(MultiDataSet) - Method in class org.deeplearning4j.datasets.iterator.file.FileMultiDataSetIterator
-
- applyPreprocessorAndSetInput(LayerWorkspaceMgr) - Method in class org.deeplearning4j.nn.graph.vertex.impl.LayerVertex
-
- applySubsampling(Sequence<T>, AtomicLong) - Method in class org.deeplearning4j.models.embeddings.learning.impl.elements.CBOW
-
- applySubsampling(Sequence<T>, AtomicLong) - Method in class org.deeplearning4j.models.embeddings.learning.impl.elements.SkipGram
-
- applySubsampling(Sequence<ShallowSequenceElement>, AtomicLong, long, double) - Static method in class org.deeplearning4j.spark.models.sequencevectors.learning.elements.BaseSparkLearningAlgorithm
-
- applyTo(List<Point>) - Method in class org.deeplearning4j.clustering.algorithm.BaseClusteringAlgorithm
-
- applyTo(List<Point>) - Method in interface org.deeplearning4j.clustering.algorithm.ClusteringAlgorithm
-
Apply a clustering
algorithm for a given result
- applyToComputationGraphConfiguration(ComputationGraphConfiguration) - Method in class org.deeplearning4j.nn.transferlearning.FineTuneConfiguration
-
- applyToMultiLayerConfiguration(MultiLayerConfiguration) - Method in class org.deeplearning4j.nn.transferlearning.FineTuneConfiguration
-
- applyToNeuralNetConfiguration(NeuralNetConfiguration) - Method in class org.deeplearning4j.nn.transferlearning.FineTuneConfiguration
-
- applyUpdate(StepFunction, INDArray, INDArray) - Method in class org.deeplearning4j.optimize.solvers.accumulation.BasicGradientsAccumulator
-
This method applies accumulated updates via given StepFunction
- applyUpdate(StepFunction, INDArray, INDArray, double) - Method in class org.deeplearning4j.optimize.solvers.accumulation.BasicGradientsAccumulator
-
This method applies accumulated updates via given StepFunction
- applyUpdate(StepFunction, INDArray, INDArray) - Method in class org.deeplearning4j.optimize.solvers.accumulation.EncodedGradientsAccumulator
-
This method applies accumulated updates via given StepFunction
- applyUpdate(StepFunction, INDArray, INDArray, double) - Method in class org.deeplearning4j.optimize.solvers.accumulation.EncodedGradientsAccumulator
-
This method applies accumulated updates via given StepFunction
- applyUpdate(StepFunction, INDArray, INDArray) - Method in interface org.deeplearning4j.optimize.solvers.accumulation.GradientsAccumulator
-
This method applies accumulated updates via given StepFunction
- applyUpdate(StepFunction, INDArray, INDArray, double) - Method in interface org.deeplearning4j.optimize.solvers.accumulation.GradientsAccumulator
-
This method applies accumulated updates via given StepFunction
- arr(INDArray) - Static method in class org.deeplearning4j.earlystopping.scorecalc.base.BaseScoreCalculator
-
- ArrayComparator() - Constructor for class org.deeplearning4j.models.embeddings.reader.impl.BasicModelUtils.ArrayComparator
-
- arrayElementsPerExample() - Method in class org.deeplearning4j.nn.conf.inputs.InputType
-
- arrayElementsPerExample() - Method in class org.deeplearning4j.nn.conf.inputs.InputType.InputTypeConvolutional
-
- arrayElementsPerExample() - Method in class org.deeplearning4j.nn.conf.inputs.InputType.InputTypeConvolutional3D
-
- arrayElementsPerExample() - Method in class org.deeplearning4j.nn.conf.inputs.InputType.InputTypeConvolutionalFlat
-
- arrayElementsPerExample() - Method in class org.deeplearning4j.nn.conf.inputs.InputType.InputTypeFeedForward
-
- arrayElementsPerExample() - Method in class org.deeplearning4j.nn.conf.inputs.InputType.InputTypeRecurrent
-
- arrayLength - Static variable in class org.ansj.library.DATDictionary
-
数组长度
- ArrayPairToPair<K> - Class in org.deeplearning4j.spark.impl.graph.scoring
-
Simple conversion function for SparkComputationGraph
- ArrayPairToPair() - Constructor for class org.deeplearning4j.spark.impl.graph.scoring.ArrayPairToPair
-
- arrayToList(byte[], int) - Static method in class org.deeplearning4j.models.word2vec.wordstore.VocabularyHolder
-
This method is used only for VocabCache compatibility purposes
- arrayToList(int[], int) - Static method in class org.deeplearning4j.models.word2vec.wordstore.VocabularyHolder
-
This method is used only for VocabCache compatibility purposes
- ArrayType - Enum in org.deeplearning4j.nn.workspace
-
Array type enumeration for use with
LayerWorkspaceMgr
Array types:
INPUT: The array set to the input field of a layer (i.e., input activations)
ACTIVATIONS: The output activations for a layer's feed-forward method
ACTIVATION_GRAD: Activation gradient arrays - aka "epsilons" - output from a layer's backprop method
FF_WORKING_MEM: Working memory during feed-forward.
- ASCIICoOccurrenceReader<T extends SequenceElement> - Class in org.deeplearning4j.models.glove.count
-
- ASCIICoOccurrenceReader(File, VocabCache<T>) - Constructor for class org.deeplearning4j.models.glove.count.ASCIICoOccurrenceReader
-
- ASCIICoOccurrenceWriter<T extends SequenceElement> - Class in org.deeplearning4j.models.glove.count
-
- ASCIICoOccurrenceWriter(File) - Constructor for class org.deeplearning4j.models.glove.count.ASCIICoOccurrenceWriter
-
- asExampleArray(Window, Word2Vec, boolean) - Static method in class org.deeplearning4j.text.movingwindow.WindowConverter
-
Converts a window (each word in the window)
in to a vector.
- asExampleMatrix(Window, Word2Vec) - Static method in class org.deeplearning4j.text.movingwindow.WindowConverter
-
Converts a window (each word in the window)
in to a vector.
- AsianPersonRecognition - Class in org.ansj.recognition.arrimpl
-
人名识别工具类
- AsianPersonRecognition() - Constructor for class org.ansj.recognition.arrimpl.AsianPersonRecognition
-
- asLabels() - Method in class org.deeplearning4j.models.sequencevectors.sequence.Sequence
-
Returns this sequence as list of labels
- assertExportSupported(JavaSparkContext) - Static method in class org.deeplearning4j.spark.impl.paramavg.util.ExportSupport
-
Verify that exporting data is supported, and throw an informative exception if not.
- assertInputSet(boolean) - Method in class org.deeplearning4j.nn.layers.AbstractLayer
-
- assertInputSet(boolean) - Method in class org.deeplearning4j.nn.layers.variational.VariationalAutoencoder
-
- assertNInNOutSet(String, String, int, int, int) - Static method in class org.deeplearning4j.nn.conf.layers.LayerValidation
-
Asserts that the layer nIn and nOut values are set for the layer
- Assets - Class in org.deeplearning4j.ui.play.staticroutes
-
Simple function for serving assets.
- Assets() - Constructor for class org.deeplearning4j.ui.play.staticroutes.Assets
-
- ASSETS_ROOT_DIRECTORY - Static variable in class org.deeplearning4j.ui.play.PlayUIServer
-
- AssignIndexFunction<T> - Class in org.deeplearning4j.spark.impl.common.repartition
-
- AssignIndexFunction(int[]) - Constructor for class org.deeplearning4j.spark.impl.common.repartition.AssignIndexFunction
-
Deprecated.
- assignVar(String, SparkConf, Class) - Static method in class org.deeplearning4j.spark.models.embeddings.word2vec.Word2VecVariables
-
Deprecated.
- asString(String) - Method in class org.deeplearning4j.spark.stats.BaseEventStats
-
- asString(String) - Method in interface org.deeplearning4j.spark.stats.EventStats
-
Get a String representation of the EventStats.
- asString(String) - Method in class org.deeplearning4j.spark.stats.ExampleCountEventStats
-
- asString(String) - Method in class org.deeplearning4j.spark.stats.PartitionCountEventStats
-
- asTokens() - Method in class org.deeplearning4j.text.movingwindow.Window
-
- AsyncDataSetIterator - Class in org.deeplearning4j.datasets.iterator
-
Async prefetching iterator wrapper for MultiDataSetIterator implementations
- AsyncDataSetIterator() - Constructor for class org.deeplearning4j.datasets.iterator.AsyncDataSetIterator
-
- AsyncDataSetIterator(DataSetIterator) - Constructor for class org.deeplearning4j.datasets.iterator.AsyncDataSetIterator
-
- AsyncDataSetIterator(DataSetIterator, int, BlockingQueue<DataSet>) - Constructor for class org.deeplearning4j.datasets.iterator.AsyncDataSetIterator
-
- AsyncDataSetIterator(DataSetIterator, int) - Constructor for class org.deeplearning4j.datasets.iterator.AsyncDataSetIterator
-
- AsyncDataSetIterator(DataSetIterator, int, boolean) - Constructor for class org.deeplearning4j.datasets.iterator.AsyncDataSetIterator
-
- AsyncDataSetIterator(DataSetIterator, int, boolean, Integer) - Constructor for class org.deeplearning4j.datasets.iterator.AsyncDataSetIterator
-
- AsyncDataSetIterator(DataSetIterator, int, boolean, DataSetCallback) - Constructor for class org.deeplearning4j.datasets.iterator.AsyncDataSetIterator
-
- AsyncDataSetIterator(DataSetIterator, int, BlockingQueue<DataSet>, boolean) - Constructor for class org.deeplearning4j.datasets.iterator.AsyncDataSetIterator
-
- AsyncDataSetIterator(DataSetIterator, int, BlockingQueue<DataSet>, boolean, DataSetCallback) - Constructor for class org.deeplearning4j.datasets.iterator.AsyncDataSetIterator
-
- AsyncDataSetIterator(DataSetIterator, int, BlockingQueue<DataSet>, boolean, DataSetCallback, Integer) - Constructor for class org.deeplearning4j.datasets.iterator.AsyncDataSetIterator
-
- AsyncDataSetIterator.AsyncPrefetchThread - Class in org.deeplearning4j.datasets.iterator
-
- AsyncIterator<T> - Class in org.deeplearning4j.parallelism
-
Asynchronous Iterator for better performance of iterators in dl4j-nn & dl4j-nlp
- AsyncIterator(Iterator<T>, int) - Constructor for class org.deeplearning4j.parallelism.AsyncIterator
-
- AsyncIterator(Iterator<T>) - Constructor for class org.deeplearning4j.parallelism.AsyncIterator
-
- asyncIterator - Variable in class org.deeplearning4j.text.documentiterator.AsyncLabelAwareIterator
-
- asyncIterators - Variable in class org.deeplearning4j.datasets.iterator.parallel.FileSplitParallelDataSetIterator
-
- asyncIterators - Variable in class org.deeplearning4j.datasets.iterator.parallel.JointParallelDataSetIterator
-
- AsyncLabelAwareIterator - Class in org.deeplearning4j.text.documentiterator
-
- AsyncLabelAwareIterator(LabelAwareIterator, int) - Constructor for class org.deeplearning4j.text.documentiterator.AsyncLabelAwareIterator
-
- AsyncMultiDataSetIterator - Class in org.deeplearning4j.datasets.iterator
-
Async prefetching iterator wrapper for MultiDataSetIterator implementations
- AsyncMultiDataSetIterator() - Constructor for class org.deeplearning4j.datasets.iterator.AsyncMultiDataSetIterator
-
- AsyncMultiDataSetIterator(MultiDataSetIterator) - Constructor for class org.deeplearning4j.datasets.iterator.AsyncMultiDataSetIterator
-
- AsyncMultiDataSetIterator(MultiDataSetIterator, int, BlockingQueue<MultiDataSet>) - Constructor for class org.deeplearning4j.datasets.iterator.AsyncMultiDataSetIterator
-
- AsyncMultiDataSetIterator(MultiDataSetIterator, int) - Constructor for class org.deeplearning4j.datasets.iterator.AsyncMultiDataSetIterator
-
- AsyncMultiDataSetIterator(MultiDataSetIterator, int, boolean) - Constructor for class org.deeplearning4j.datasets.iterator.AsyncMultiDataSetIterator
-
- AsyncMultiDataSetIterator(MultiDataSetIterator, int, boolean, Integer) - Constructor for class org.deeplearning4j.datasets.iterator.AsyncMultiDataSetIterator
-
- AsyncMultiDataSetIterator(MultiDataSetIterator, int, BlockingQueue<MultiDataSet>, boolean) - Constructor for class org.deeplearning4j.datasets.iterator.AsyncMultiDataSetIterator
-
- AsyncMultiDataSetIterator(MultiDataSetIterator, int, BlockingQueue<MultiDataSet>, boolean, DataSetCallback) - Constructor for class org.deeplearning4j.datasets.iterator.AsyncMultiDataSetIterator
-
- AsyncMultiDataSetIterator(MultiDataSetIterator, int, BlockingQueue<MultiDataSet>, boolean, DataSetCallback, Integer) - Constructor for class org.deeplearning4j.datasets.iterator.AsyncMultiDataSetIterator
-
- AsyncMultiDataSetIterator.AsyncPrefetchThread - Class in org.deeplearning4j.datasets.iterator
-
- AsyncPrefetchThread(BlockingQueue<DataSet>, DataSetIterator, DataSet, MemoryWorkspace) - Constructor for class org.deeplearning4j.datasets.iterator.AsyncDataSetIterator.AsyncPrefetchThread
-
- AsyncPrefetchThread(BlockingQueue<MultiDataSet>, MultiDataSetIterator, MultiDataSet) - Constructor for class org.deeplearning4j.datasets.iterator.AsyncMultiDataSetIterator.AsyncPrefetchThread
-
- AsyncSequencer(SequenceIterator<T>, Collection<String>) - Constructor for class org.deeplearning4j.models.sequencevectors.SequenceVectors.AsyncSequencer
-
- AsyncShieldDataSetIterator - Class in org.deeplearning4j.datasets.iterator
-
This wrapper takes your existing DataSetIterator implementation and prevents asynchronous prefetch
- AsyncShieldDataSetIterator(DataSetIterator) - Constructor for class org.deeplearning4j.datasets.iterator.AsyncShieldDataSetIterator
-
- AsyncShieldMultiDataSetIterator - Class in org.deeplearning4j.datasets.iterator
-
This wrapper takes your existing MultiDataSetIterator implementation and prevents asynchronous prefetch
- AsyncShieldMultiDataSetIterator(MultiDataSetIterator) - Constructor for class org.deeplearning4j.datasets.iterator.AsyncShieldMultiDataSetIterator
-
- asyncSupported() - Method in class org.deeplearning4j.datasets.datavec.RecordReaderDataSetIterator
-
- asyncSupported() - Method in class org.deeplearning4j.datasets.datavec.RecordReaderMultiDataSetIterator
-
- asyncSupported() - Method in class org.deeplearning4j.datasets.datavec.SequenceRecordReaderDataSetIterator
-
- asyncSupported() - Method in class org.deeplearning4j.datasets.iterator.AbstractDataSetIterator
-
- asyncSupported() - Method in class org.deeplearning4j.datasets.iterator.AsyncDataSetIterator
-
Does this DataSetIterator support asynchronous prefetching of multiple DataSet objects?
Most DataSetIterators do, but in some cases it may not make sense to wrap this iterator in an
iterator that does asynchronous prefetching.
- asyncSupported() - Method in class org.deeplearning4j.datasets.iterator.AsyncMultiDataSetIterator
-
Does this DataSetIterator support asynchronous prefetching of multiple DataSet objects?
Most DataSetIterators do, but in some cases it may not make sense to wrap this iterator in an
iterator that does asynchronous prefetching.
- asyncSupported() - Method in class org.deeplearning4j.datasets.iterator.AsyncShieldDataSetIterator
-
Does this DataSetIterator support asynchronous prefetching of multiple DataSet objects?
PLEASE NOTE: This iterator ALWAYS returns FALSE
- asyncSupported() - Method in class org.deeplearning4j.datasets.iterator.AsyncShieldMultiDataSetIterator
-
/**
Does this DataSetIterator support asynchronous prefetching of multiple DataSet objects?
PLEASE NOTE: This iterator ALWAYS returns FALSE
- asyncSupported() - Method in class org.deeplearning4j.datasets.iterator.BaseDatasetIterator
-
- asyncSupported() - Method in class org.deeplearning4j.datasets.iterator.EarlyTerminationDataSetIterator
-
- asyncSupported() - Method in class org.deeplearning4j.datasets.iterator.EarlyTerminationMultiDataSetIterator
-
- asyncSupported() - Method in class org.deeplearning4j.datasets.iterator.ExistingDataSetIterator
-
- asyncSupported() - Method in class org.deeplearning4j.datasets.iterator.file.BaseFileIterator
-
- asyncSupported() - Method in class org.deeplearning4j.datasets.iterator.FileSplitDataSetIterator
-
- asyncSupported() - Method in class org.deeplearning4j.datasets.iterator.impl.BenchmarkDataSetIterator
-
- asyncSupported() - Method in class org.deeplearning4j.datasets.iterator.impl.BenchmarkMultiDataSetIterator
-
- asyncSupported() - Method in class org.deeplearning4j.datasets.iterator.impl.CifarDataSetIterator
-
- asyncSupported() - Method in class org.deeplearning4j.datasets.iterator.impl.ListDataSetIterator
-
- asyncSupported() - Method in class org.deeplearning4j.datasets.iterator.impl.MultiDataSetIteratorAdapter
-
- asyncSupported() - Method in class org.deeplearning4j.datasets.iterator.impl.SingletonMultiDataSetIterator
-
- asyncSupported() - Method in class org.deeplearning4j.datasets.iterator.IteratorDataSetIterator
-
- asyncSupported() - Method in class org.deeplearning4j.datasets.iterator.IteratorMultiDataSetIterator
-
- asyncSupported() - Method in class org.deeplearning4j.datasets.iterator.MultiDataSetWrapperIterator
-
- asyncSupported() - Method in class org.deeplearning4j.datasets.iterator.MultipleEpochsIterator
-
Deprecated.
- asyncSupported() - Method in class org.deeplearning4j.datasets.iterator.parallel.BaseParallelDataSetIterator
-
- asyncSupported() - Method in class org.deeplearning4j.datasets.iterator.ReconstructionDataSetIterator
-
- asyncSupported() - Method in class org.deeplearning4j.datasets.iterator.SamplingDataSetIterator
-
- asyncSupported() - Method in class org.deeplearning4j.datasets.iterator.WorkspacesShieldDataSetIterator
-
- asyncSupported() - Method in class org.deeplearning4j.datasets.test.TestDataSetIterator
-
- asyncSupported() - Method in class org.deeplearning4j.iterator.CnnSentenceDataSetIterator
-
- asyncSupported() - Method in class org.deeplearning4j.models.word2vec.iterator.Word2VecDataSetIterator
-
- asyncSupported() - Method in class org.deeplearning4j.spark.iterator.BaseDataSetIterator
-
- asyncSupported() - Method in class org.deeplearning4j.spark.iterator.PathSparkMultiDataSetIterator
-
- asyncSupported() - Method in class org.deeplearning4j.spark.iterator.PortableDataStreamMultiDataSetIterator
-
- asyncSupported() - Method in class org.deeplearning4j.spark.parameterserver.iterators.VirtualDataSetIterator
-
- asyncSupported() - Method in class org.deeplearning4j.spark.parameterserver.iterators.VirtualMultiDataSetIterator
-
- atomicBoundary - Variable in class org.deeplearning4j.optimize.solvers.accumulation.EncodingHandler
-
- attach(StatsStorage) - Method in class org.deeplearning4j.ui.api.UIServer
-
Attach the given StatsStorage instance to the UI, so the data can be visualized
- attach(StatsStorage) - Method in class org.deeplearning4j.ui.play.PlayUIServer
-
- attachContext(VoidConfiguration, TrainingDriver<? extends TrainingMessage>, Clipboard, Transport, Storage, NodeRole, short) - Method in class org.deeplearning4j.spark.parameterserver.networking.messages.SilentUpdatesMessage
-
- attachDS(Iterator<DataSet>) - Method in class org.deeplearning4j.spark.parameterserver.pw.SharedTrainingWrapper
-
This method registers given Iterable in VirtualDataSetIterator
- attachMDS(Iterator<MultiDataSet>) - Method in class org.deeplearning4j.spark.parameterserver.pw.SharedTrainingWrapper
-
This method registers given Iterable in VirtualMultiDataSetIterator
- attachThread(int) - Method in class org.deeplearning4j.datasets.iterator.parallel.BaseParallelDataSetIterator
-
- attachThread(int) - Method in class org.deeplearning4j.spark.parameterserver.iterators.VirtualMultiDataSetIterator
-
- authToken - Variable in class org.deeplearning4j.nearestneighbor.client.NearestNeighborsClient
-
- AutoEncoder - Class in org.deeplearning4j.nn.conf.layers
-
Autoencoder.
- AutoEncoder - Class in org.deeplearning4j.nn.layers.feedforward.autoencoder
-
Autoencoder.
- AutoEncoder(NeuralNetConfiguration) - Constructor for class org.deeplearning4j.nn.layers.feedforward.autoencoder.AutoEncoder
-
- AutoEncoder(NeuralNetConfiguration, INDArray) - Constructor for class org.deeplearning4j.nn.layers.feedforward.autoencoder.AutoEncoder
-
- AutoEncoder.Builder - Class in org.deeplearning4j.nn.conf.layers
-
- AutoencoderScoreCalculator - Class in org.deeplearning4j.earlystopping.scorecalc
-
Score function for a MultiLayerNetwork or ComputationGraph with a single
AutoEncoder layer.
- AutoencoderScoreCalculator(RegressionEvaluation.Metric, DataSetIterator) - Constructor for class org.deeplearning4j.earlystopping.scorecalc.AutoencoderScoreCalculator
-
- availableCheckpoints() - Method in class org.deeplearning4j.optimize.listeners.checkpoint.CheckpointListener
-
List all available checkpoints.
- average - Variable in class org.deeplearning4j.earlystopping.scorecalc.VAEReconProbScoreCalculator
-
- averageAccuracy() - Method in class org.deeplearning4j.eval.EvaluationBinary
-
- averagecorrelationR2() - Method in class org.deeplearning4j.eval.RegressionEvaluation
-
- averageF1() - Method in class org.deeplearning4j.eval.EvaluationBinary
-
- averageF1NumClassesExcluded() - Method in class org.deeplearning4j.eval.Evaluation
-
When calculating the (macro) average F1, how many classes are excluded from the average due to
no predictions – i.e., F1 would be calculated from a precision or recall of 0/0
- averageFBetaNumClassesExcluded() - Method in class org.deeplearning4j.eval.Evaluation
-
When calculating the (macro) average FBeta, how many classes are excluded from the average due to
no predictions – i.e., FBeta would be calculated from a precision or recall of 0/0
- averageMeanAbsoluteError() - Method in class org.deeplearning4j.eval.RegressionEvaluation
-
Average MAE across all columns
- averageMeanSquaredError() - Method in class org.deeplearning4j.eval.RegressionEvaluation
-
Average MSE across all columns
- averagePearsonCorrelation() - Method in class org.deeplearning4j.eval.RegressionEvaluation
-
Average Pearson Correlation Coefficient across all columns
- averagePrecision() - Method in class org.deeplearning4j.eval.EvaluationBinary
-
- averagePrecisionNumClassesExcluded() - Method in class org.deeplearning4j.eval.Evaluation
-
When calculating the (macro) average precision, how many classes are excluded from the average due to
no predictions – i.e., precision would be the edge case of 0/0
- averageRecall() - Method in class org.deeplearning4j.eval.EvaluationBinary
-
- averageRecallNumClassesExcluded() - Method in class org.deeplearning4j.eval.Evaluation
-
When calculating the (macro) average Recall, how many classes are excluded from the average due to
no predictions – i.e., recall would be the edge case of 0/0
- averagerelativeSquaredError() - Method in class org.deeplearning4j.eval.RegressionEvaluation
-
Average RSE across all columns
- averagerootMeanSquaredError() - Method in class org.deeplearning4j.eval.RegressionEvaluation
-
Average RMSE across all columns
- averageRSquared() - Method in class org.deeplearning4j.eval.RegressionEvaluation
-
Average R2 across all columns
- averageUpdaters - Variable in class org.deeplearning4j.parallelism.ParallelWrapper
-
- averageUpdaters - Variable in class org.deeplearning4j.parallelism.ParallelWrapper.Builder
-
- averageUpdaters(boolean) - Method in class org.deeplearning4j.parallelism.ParallelWrapper.Builder
-
This method enables/disables updaters averaging.
- averagingFrequency - Variable in class org.deeplearning4j.parallelism.ParallelWrapper
-
- averagingFrequency - Variable in class org.deeplearning4j.parallelism.ParallelWrapper.Builder
-
- averagingFrequency(int) - Method in class org.deeplearning4j.parallelism.ParallelWrapper.Builder
-
Model averaging frequency.
- averagingFrequency(int) - Method in class org.deeplearning4j.parallelism.parameterserver.ParameterServerTrainer.ParameterServerTrainerBuilder
-
- averagingFrequency - Variable in class org.deeplearning4j.parallelism.trainer.DefaultTrainer
-
- averagingFrequency - Variable in class org.deeplearning4j.spark.impl.paramavg.ParameterAveragingTrainingMaster
-
- averagingFrequency - Variable in class org.deeplearning4j.spark.impl.paramavg.ParameterAveragingTrainingMaster.Builder
-
- averagingFrequency(int) - Method in class org.deeplearning4j.spark.impl.paramavg.ParameterAveragingTrainingMaster.Builder
-
Frequency with which to average worker parameters.
Note: Too high or too low can be bad for different reasons.
- Too low (such as 1) can result in a lot of network traffic
- Too high (>> 20 or so) can result in accuracy issues or problems with network convergence
- averagingRequired() - Method in class org.deeplearning4j.parallelism.trainer.DefaultTrainer
-
- averagingRequired() - Method in class org.deeplearning4j.parallelism.trainer.SymmetricTrainer
-
- averagingRequired() - Method in interface org.deeplearning4j.parallelism.trainer.Trainer
-
This method returns TRUE if this Trainer implementation assumes periodic aver
- avgPool7x7(int) - Static method in class org.deeplearning4j.zoo.model.helper.FaceNetHelper
-
- avgPoolNxN(int, int) - Static method in class org.deeplearning4j.zoo.model.helper.FaceNetHelper
-
- awaitDone() - Method in class org.deeplearning4j.models.word2vec.wordstore.VocabConstructor.VocabRunnable
-
- AWS_ACCESS_KEY - Static variable in class org.deeplearning4j.aws.s3.BaseS3
-
- AWS_SECRET_KEY - Static variable in class org.deeplearning4j.aws.s3.BaseS3
-
- awsRegion(String) - Method in class org.deeplearning4j.aws.emr.SparkEMRClient.Builder
-
Defines the EMR cluster's region
See https://docs.aws.amazon.com/general/latest/gr/rande.html
- axisStrokeWidth - Variable in class org.deeplearning4j.ui.components.chart.style.StyleChart
-
- axisStrokeWidth - Variable in class org.deeplearning4j.ui.components.chart.style.StyleChart.Builder
-
- axisStrokeWidth(double) - Method in class org.deeplearning4j.ui.components.chart.style.StyleChart.Builder
-
- B - Static variable in class org.ansj.app.crf.Config
-
- B - Static variable in class org.ansj.util.Graph
-
- b(double) - Method in class org.deeplearning4j.nn.conf.dropout.AlphaDropout
-
- backedIterator - Variable in class org.deeplearning4j.datasets.iterator.AsyncDataSetIterator
-
- backedIterator - Variable in class org.deeplearning4j.datasets.iterator.AsyncMultiDataSetIterator
-
- backedIterator - Variable in class org.deeplearning4j.datasets.iterator.DataSetIteratorSplitter
-
- backedIterator - Variable in class org.deeplearning4j.datasets.iterator.MultiDataSetIteratorSplitter
-
- backedIterator - Variable in class org.deeplearning4j.text.documentiterator.AsyncLabelAwareIterator
-
- backendIterator - Variable in class org.deeplearning4j.text.documentiterator.BasicLabelAwareIterator
-
- backendIterator - Variable in class org.deeplearning4j.text.documentiterator.interoperability.DocumentIteratorConverter
-
- backgroundColor - Variable in class org.deeplearning4j.ui.api.Style
-
- backgroundColor - Variable in class org.deeplearning4j.ui.api.Style.Builder
-
- backgroundColor(Color) - Method in class org.deeplearning4j.ui.api.Style.Builder
-
- backgroundColor(String) - Method in class org.deeplearning4j.ui.api.Style.Builder
-
- backgroundColor(Color) - Method in class org.deeplearning4j.ui.components.table.style.StyleTable.Builder
-
- backgroundColor(String) - Method in class org.deeplearning4j.ui.components.table.style.StyleTable.Builder
-
- backingQueue - Variable in class org.deeplearning4j.optimize.solvers.accumulation.FancyBlockingQueue
-
- backingQueues - Variable in class org.deeplearning4j.parallelism.MagicQueue
-
Deprecated.
- backprop - Variable in class org.deeplearning4j.nn.conf.ComputationGraphConfiguration
-
- backprop - Variable in class org.deeplearning4j.nn.conf.ComputationGraphConfiguration.GraphBuilder
-
- backprop(boolean) - Method in class org.deeplearning4j.nn.conf.ComputationGraphConfiguration.GraphBuilder
-
Whether to do back prop (standard supervised learning) or not
- backprop(INDArray, int, LayerWorkspaceMgr) - Method in interface org.deeplearning4j.nn.conf.InputPreProcessor
-
Reverse the preProcess during backprop.
- backprop - Variable in class org.deeplearning4j.nn.conf.MultiLayerConfiguration
-
- backprop - Variable in class org.deeplearning4j.nn.conf.MultiLayerConfiguration.Builder
-
- backprop(boolean) - Method in class org.deeplearning4j.nn.conf.MultiLayerConfiguration.Builder
-
Whether to do back prop or not
- backprop(boolean) - Method in class org.deeplearning4j.nn.conf.NeuralNetConfiguration.ListBuilder
-
- backprop(INDArray, int, LayerWorkspaceMgr) - Method in class org.deeplearning4j.nn.conf.preprocessor.BinomialSamplingPreProcessor
-
- backprop(INDArray, int, LayerWorkspaceMgr) - Method in class org.deeplearning4j.nn.conf.preprocessor.Cnn3DToFeedForwardPreProcessor
-
- backprop(INDArray, int, LayerWorkspaceMgr) - Method in class org.deeplearning4j.nn.conf.preprocessor.CnnToFeedForwardPreProcessor
-
- backprop(INDArray, int, LayerWorkspaceMgr) - Method in class org.deeplearning4j.nn.conf.preprocessor.CnnToRnnPreProcessor
-
- backprop(INDArray, int, LayerWorkspaceMgr) - Method in class org.deeplearning4j.nn.conf.preprocessor.ComposableInputPreProcessor
-
- backprop(INDArray, int, LayerWorkspaceMgr) - Method in class org.deeplearning4j.nn.conf.preprocessor.FeedForwardToCnn3DPreProcessor
-
- backprop(INDArray, int, LayerWorkspaceMgr) - Method in class org.deeplearning4j.nn.conf.preprocessor.FeedForwardToCnnPreProcessor
-
- backprop(INDArray, int, LayerWorkspaceMgr) - Method in class org.deeplearning4j.nn.conf.preprocessor.FeedForwardToRnnPreProcessor
-
- backprop(INDArray, int, LayerWorkspaceMgr) - Method in class org.deeplearning4j.nn.conf.preprocessor.RnnToCnnPreProcessor
-
- backprop(INDArray, int, LayerWorkspaceMgr) - Method in class org.deeplearning4j.nn.conf.preprocessor.RnnToFeedForwardPreProcessor
-
- backprop(INDArray, int, LayerWorkspaceMgr) - Method in class org.deeplearning4j.nn.conf.preprocessor.UnitVarianceProcessor
-
- backprop(INDArray, int, LayerWorkspaceMgr) - Method in class org.deeplearning4j.nn.conf.preprocessor.ZeroMeanAndUnitVariancePreProcessor
-
- backprop(INDArray, int, LayerWorkspaceMgr) - Method in class org.deeplearning4j.nn.conf.preprocessor.ZeroMeanPrePreProcessor
-
- backprop(INDArray, int, LayerWorkspaceMgr) - Method in class org.deeplearning4j.nn.modelimport.keras.preprocessors.KerasFlattenRnnPreprocessor
-
- backprop(INDArray, int, LayerWorkspaceMgr) - Method in class org.deeplearning4j.nn.modelimport.keras.preprocessors.PermutePreprocessor
-
- backprop(INDArray, int, LayerWorkspaceMgr) - Method in class org.deeplearning4j.nn.modelimport.keras.preprocessors.ReshapePreprocessor
-
- backprop(INDArray, int, LayerWorkspaceMgr) - Method in class org.deeplearning4j.nn.modelimport.keras.preprocessors.TensorFlowCnnToFeedForwardPreProcessor
-
- backprop - Variable in class org.deeplearning4j.nn.transferlearning.FineTuneConfiguration
-
- backprop(boolean) - Method in class org.deeplearning4j.nn.transferlearning.FineTuneConfiguration.Builder
-
- backpropGradient(INDArray, LayerWorkspaceMgr) - Method in interface org.deeplearning4j.nn.api.Layer
-
Calculate the gradient relative to the error in the next layer
- backpropGradient(INDArray...) - Method in class org.deeplearning4j.nn.graph.ComputationGraph
-
Calculate the gradient of the network with respect to some external errors.
- backpropGradient(INDArray, LayerWorkspaceMgr) - Method in class org.deeplearning4j.nn.layers.ActivationLayer
-
- backpropGradient(INDArray, LayerWorkspaceMgr) - Method in class org.deeplearning4j.nn.layers.BaseLayer
-
- backpropGradient(INDArray, LayerWorkspaceMgr) - Method in class org.deeplearning4j.nn.layers.BaseOutputLayer
-
- backpropGradient(INDArray, LayerWorkspaceMgr) - Method in class org.deeplearning4j.nn.layers.BasePretrainNetwork
-
- backpropGradient(INDArray, LayerWorkspaceMgr) - Method in class org.deeplearning4j.nn.layers.convolution.CnnLossLayer
-
- backpropGradient(INDArray, LayerWorkspaceMgr) - Method in class org.deeplearning4j.nn.layers.convolution.Convolution1DLayer
-
- backpropGradient(INDArray, LayerWorkspaceMgr) - Method in class org.deeplearning4j.nn.layers.convolution.Convolution3DLayer
-
- backpropGradient(INDArray, INDArray, INDArray, int[], int[], int[], INDArray, INDArray, IActivation, ConvolutionLayer.AlgoMode, ConvolutionLayer.BwdFilterAlgo, ConvolutionLayer.BwdDataAlgo, ConvolutionMode, int[], LayerWorkspaceMgr) - Method in interface org.deeplearning4j.nn.layers.convolution.ConvolutionHelper
-
- backpropGradient(INDArray, LayerWorkspaceMgr) - Method in class org.deeplearning4j.nn.layers.convolution.ConvolutionLayer
-
- backpropGradient(INDArray, LayerWorkspaceMgr) - Method in class org.deeplearning4j.nn.layers.convolution.Cropping1DLayer
-
- backpropGradient(INDArray, LayerWorkspaceMgr) - Method in class org.deeplearning4j.nn.layers.convolution.Cropping2DLayer
-
- backpropGradient(INDArray, LayerWorkspaceMgr) - Method in class org.deeplearning4j.nn.layers.convolution.Cropping3DLayer
-
- backpropGradient(INDArray, INDArray, INDArray, int[], int[], int[], INDArray, INDArray, IActivation, ConvolutionLayer.AlgoMode, ConvolutionLayer.BwdFilterAlgo, ConvolutionLayer.BwdDataAlgo, ConvolutionMode, int[], LayerWorkspaceMgr) - Method in class org.deeplearning4j.nn.layers.convolution.CudnnConvolutionHelper
-
- backpropGradient(INDArray, LayerWorkspaceMgr) - Method in class org.deeplearning4j.nn.layers.convolution.Deconvolution2DLayer
-
- backpropGradient(INDArray, LayerWorkspaceMgr) - Method in class org.deeplearning4j.nn.layers.convolution.DepthwiseConvolution2DLayer
-
- backpropGradient(INDArray, LayerWorkspaceMgr) - Method in class org.deeplearning4j.nn.layers.convolution.SeparableConvolution2DLayer
-
- backpropGradient(INDArray, LayerWorkspaceMgr) - Method in class org.deeplearning4j.nn.layers.convolution.SpaceToBatch
-
- backpropGradient(INDArray, LayerWorkspaceMgr) - Method in class org.deeplearning4j.nn.layers.convolution.SpaceToDepth
-
- backpropGradient(INDArray, INDArray, int[], int[], int[], PoolingType, ConvolutionMode, int[], LayerWorkspaceMgr) - Method in class org.deeplearning4j.nn.layers.convolution.subsampling.CudnnSubsamplingHelper
-
- backpropGradient(INDArray, LayerWorkspaceMgr) - Method in class org.deeplearning4j.nn.layers.convolution.subsampling.Subsampling1DLayer
-
- backpropGradient(INDArray, LayerWorkspaceMgr) - Method in class org.deeplearning4j.nn.layers.convolution.subsampling.Subsampling3DLayer
-
- backpropGradient(INDArray, INDArray, int[], int[], int[], PoolingType, ConvolutionMode, int[], LayerWorkspaceMgr) - Method in interface org.deeplearning4j.nn.layers.convolution.subsampling.SubsamplingHelper
-
- backpropGradient(INDArray, LayerWorkspaceMgr) - Method in class org.deeplearning4j.nn.layers.convolution.subsampling.SubsamplingLayer
-
- backpropGradient(INDArray, LayerWorkspaceMgr) - Method in class org.deeplearning4j.nn.layers.convolution.upsampling.Upsampling1D
-
- backpropGradient(INDArray, LayerWorkspaceMgr) - Method in class org.deeplearning4j.nn.layers.convolution.upsampling.Upsampling2D
-
- backpropGradient(INDArray, LayerWorkspaceMgr) - Method in class org.deeplearning4j.nn.layers.convolution.upsampling.Upsampling3D
-
- backpropGradient(INDArray, LayerWorkspaceMgr) - Method in class org.deeplearning4j.nn.layers.convolution.ZeroPadding1DLayer
-
- backpropGradient(INDArray, LayerWorkspaceMgr) - Method in class org.deeplearning4j.nn.layers.convolution.ZeroPadding3DLayer
-
- backpropGradient(INDArray, LayerWorkspaceMgr) - Method in class org.deeplearning4j.nn.layers.convolution.ZeroPaddingLayer
-
- backpropGradient(INDArray, LayerWorkspaceMgr) - Method in class org.deeplearning4j.nn.layers.DropoutLayer
-
- backpropGradient(INDArray, LayerWorkspaceMgr) - Method in class org.deeplearning4j.nn.layers.feedforward.elementwise.ElementWiseMultiplicationLayer
-
- backpropGradient(INDArray, LayerWorkspaceMgr) - Method in class org.deeplearning4j.nn.layers.feedforward.embedding.EmbeddingLayer
-
- backpropGradient(INDArray, LayerWorkspaceMgr) - Method in class org.deeplearning4j.nn.layers.feedforward.embedding.EmbeddingSequenceLayer
-
- backpropGradient(INDArray, LayerWorkspaceMgr) - Method in class org.deeplearning4j.nn.layers.FrozenLayer
-
- backpropGradient(INDArray, LayerWorkspaceMgr) - Method in class org.deeplearning4j.nn.layers.FrozenLayerWithBackprop
-
- backpropGradient(INDArray, LayerWorkspaceMgr) - Method in class org.deeplearning4j.nn.layers.LossLayer
-
- backpropGradient(INDArray, LayerWorkspaceMgr) - Method in class org.deeplearning4j.nn.layers.normalization.BatchNormalization
-
- backpropGradient(INDArray, INDArray, int[], INDArray, INDArray, INDArray, double, LayerWorkspaceMgr) - Method in interface org.deeplearning4j.nn.layers.normalization.BatchNormalizationHelper
-
- backpropGradient(INDArray, INDArray, int[], INDArray, INDArray, INDArray, double, LayerWorkspaceMgr) - Method in class org.deeplearning4j.nn.layers.normalization.CudnnBatchNormalizationHelper
-
- backpropGradient(INDArray, INDArray, double, double, double, double, LayerWorkspaceMgr) - Method in class org.deeplearning4j.nn.layers.normalization.CudnnLocalResponseNormalizationHelper
-
- backpropGradient(INDArray, LayerWorkspaceMgr) - Method in class org.deeplearning4j.nn.layers.normalization.LocalResponseNormalization
-
- backpropGradient(INDArray, INDArray, double, double, double, double, LayerWorkspaceMgr) - Method in interface org.deeplearning4j.nn.layers.normalization.LocalResponseNormalizationHelper
-
- backpropGradient(INDArray, LayerWorkspaceMgr) - Method in class org.deeplearning4j.nn.layers.objdetect.Yolo2OutputLayer
-
- backpropGradient(INDArray, LayerWorkspaceMgr) - Method in class org.deeplearning4j.nn.layers.ocnn.OCNNOutputLayer
-
- backpropGradient(INDArray, LayerWorkspaceMgr) - Method in class org.deeplearning4j.nn.layers.pooling.GlobalPoolingLayer
-
- backpropGradient(INDArray, LayerWorkspaceMgr) - Method in class org.deeplearning4j.nn.layers.recurrent.BidirectionalLayer
-
- backpropGradient(NeuralNetConfiguration, IActivation, INDArray, INDArray, INDArray, INDArray, boolean, int, FwdPassReturn, boolean, String, String, String, Map<String, INDArray>, INDArray, boolean, LayerWorkspaceMgr) - Method in class org.deeplearning4j.nn.layers.recurrent.CudnnLSTMHelper
-
- backpropGradient(INDArray, LayerWorkspaceMgr) - Method in class org.deeplearning4j.nn.layers.recurrent.GravesBidirectionalLSTM
-
- backpropGradient(INDArray, LayerWorkspaceMgr) - Method in class org.deeplearning4j.nn.layers.recurrent.GravesLSTM
-
- backpropGradient(INDArray, LayerWorkspaceMgr) - Method in class org.deeplearning4j.nn.layers.recurrent.LastTimeStepLayer
-
- backpropGradient(INDArray, LayerWorkspaceMgr) - Method in class org.deeplearning4j.nn.layers.recurrent.LSTM
-
- backpropGradient(NeuralNetConfiguration, IActivation, INDArray, INDArray, INDArray, INDArray, boolean, int, FwdPassReturn, boolean, String, String, String, Map<String, INDArray>, INDArray, boolean, LayerWorkspaceMgr) - Method in interface org.deeplearning4j.nn.layers.recurrent.LSTMHelper
-
- backpropGradient(INDArray, LayerWorkspaceMgr) - Method in class org.deeplearning4j.nn.layers.recurrent.MaskZeroLayer
-
- backpropGradient(INDArray, LayerWorkspaceMgr) - Method in class org.deeplearning4j.nn.layers.recurrent.RnnLossLayer
-
- backpropGradient(INDArray, LayerWorkspaceMgr) - Method in class org.deeplearning4j.nn.layers.recurrent.RnnOutputLayer
-
- backpropGradient(INDArray, LayerWorkspaceMgr) - Method in class org.deeplearning4j.nn.layers.recurrent.SimpleRnn
-
- backpropGradient(INDArray, LayerWorkspaceMgr) - Method in class org.deeplearning4j.nn.layers.samediff.SameDiffLayer
-
- backpropGradient(INDArray, LayerWorkspaceMgr) - Method in class org.deeplearning4j.nn.layers.training.CenterLossOutputLayer
-
- backpropGradient(INDArray, LayerWorkspaceMgr) - Method in class org.deeplearning4j.nn.layers.util.MaskLayer
-
- backpropGradient(INDArray, LayerWorkspaceMgr) - Method in class org.deeplearning4j.nn.layers.variational.VariationalAutoencoder
-
- backpropGradient(INDArray, LayerWorkspaceMgr) - Method in class org.deeplearning4j.nn.layers.wrapper.BaseWrapperLayer
-
- backpropGradient(INDArray, LayerWorkspaceMgr) - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
-
- backpropGradientHelper(NeuralNetConfiguration, IActivation, INDArray, INDArray, INDArray, INDArray, boolean, int, FwdPassReturn, boolean, String, String, String, Map<String, INDArray>, INDArray, boolean, LSTMHelper, LayerWorkspaceMgr) - Static method in class org.deeplearning4j.nn.layers.recurrent.LSTMHelpers
-
- BackpropType - Enum in org.deeplearning4j.nn.conf
-
Defines the type of backpropagation.
- backpropType - Variable in class org.deeplearning4j.nn.conf.ComputationGraphConfiguration
-
- backpropType - Variable in class org.deeplearning4j.nn.conf.ComputationGraphConfiguration.GraphBuilder
-
- backpropType(BackpropType) - Method in class org.deeplearning4j.nn.conf.ComputationGraphConfiguration.GraphBuilder
-
The type of backprop.
- backpropType - Variable in class org.deeplearning4j.nn.conf.MultiLayerConfiguration
-
- backpropType - Variable in class org.deeplearning4j.nn.conf.MultiLayerConfiguration.Builder
-
- backpropType(BackpropType) - Method in class org.deeplearning4j.nn.conf.MultiLayerConfiguration.Builder
-
The type of backprop.
- backpropType - Variable in class org.deeplearning4j.nn.transferlearning.FineTuneConfiguration
-
- backpropType(BackpropType) - Method in class org.deeplearning4j.nn.transferlearning.FineTuneConfiguration.Builder
-
The type of backprop.
- BackTrackLineSearch - Class in org.deeplearning4j.optimize.solvers
-
- BackTrackLineSearch(Model, StepFunction, ConvexOptimizer) - Constructor for class org.deeplearning4j.optimize.solvers.BackTrackLineSearch
-
- BackTrackLineSearch(Model, ConvexOptimizer) - Constructor for class org.deeplearning4j.optimize.solvers.BackTrackLineSearch
-
- BACKWARD_PREFIX - Static variable in class org.deeplearning4j.nn.params.BidirectionalParamInitializer
-
- BagOfWordsVectorizer - Class in org.deeplearning4j.bagofwords.vectorizer
-
- BagOfWordsVectorizer() - Constructor for class org.deeplearning4j.bagofwords.vectorizer.BagOfWordsVectorizer
-
- BagOfWordsVectorizer.Builder - Class in org.deeplearning4j.bagofwords.vectorizer
-
- BalancedPartitioner - Class in org.deeplearning4j.spark.impl.common.repartition
-
This is a custom partitioner (used in conjunction with
AssignIndexFunction to repartition a RDD.
- BalancedPartitioner(int, int, int) - Constructor for class org.deeplearning4j.spark.impl.common.repartition.BalancedPartitioner
-
- balancedRandomSplit(int, int, JavaRDD<T>) - Static method in class org.deeplearning4j.spark.util.SparkUtils
-
Random split the specified RDD into a number of RDDs, where each has numObjectsPerSplit in them.
- balancedRandomSplit(int, int, JavaRDD<T>, long) - Static method in class org.deeplearning4j.spark.util.SparkUtils
-
- balancedRandomSplit(int, int, JavaPairRDD<T, U>) - Static method in class org.deeplearning4j.spark.util.SparkUtils
-
- balancedRandomSplit(int, int, JavaPairRDD<T, U>, long) - Static method in class org.deeplearning4j.spark.util.SparkUtils
-
- BarnesHutTsne - Class in org.deeplearning4j.plot
-
Barnes hut algorithm for TSNE, uses a dual tree approximation approach.
- BarnesHutTsne(int, String, double, boolean, int, double, double, double, double, int, boolean, int, double, double, boolean, double, TrainingListener, double, int) - Constructor for class org.deeplearning4j.plot.BarnesHutTsne
-
- BarnesHutTsne.Builder - Class in org.deeplearning4j.plot
-
- barrier - Variable in class org.deeplearning4j.optimize.solvers.accumulation.BasicGradientsAccumulator
-
- barrier - Variable in class org.deeplearning4j.optimize.solvers.accumulation.EncodedGradientsAccumulator
-
- barrier - Variable in class org.deeplearning4j.optimize.solvers.accumulation.FancyBlockingQueue
-
- Base64NDArrayBody - Class in org.deeplearning4j.nearestneighbor.model
-
Created by agibsonccc on 12/24/16.
- Base64NDArrayBody() - Constructor for class org.deeplearning4j.nearestneighbor.model.Base64NDArrayBody
-
- BASE_DIR - Variable in class org.deeplearning4j.base.MnistFetcher
-
- BASE_FORM - Static variable in class com.atilika.kuromoji.ipadic.compile.DictionaryEntry
-
- BaseAnalysis - Class in org.ansj.splitWord.analysis
-
基本的分词.只做了.ngram模型.和数字发现.其他一律不管
- BaseAnalysis() - Constructor for class org.ansj.splitWord.analysis.BaseAnalysis
-
- BaseAnalysis(Reader) - Constructor for class org.ansj.splitWord.analysis.BaseAnalysis
-
- BaseClusteringAlgorithm - Class in org.deeplearning4j.clustering.algorithm
-
adapted to ndarray matrices
- BaseClusteringAlgorithm(ClusteringStrategy) - Constructor for class org.deeplearning4j.clustering.algorithm.BaseClusteringAlgorithm
-
- BaseClusteringStrategy - Class in org.deeplearning4j.clustering.strategy
-
- BaseClusteringStrategy(ClusteringStrategyType, Integer, String, boolean, boolean) - Constructor for class org.deeplearning4j.clustering.strategy.BaseClusteringStrategy
-
- BaseClusteringStrategy(ClusteringStrategyType, int, String, boolean) - Constructor for class org.deeplearning4j.clustering.strategy.BaseClusteringStrategy
-
- BaseCollectionStatsStorage - Class in org.deeplearning4j.ui.storage
-
An implementation of the
StatsStorage interface, backed by MapDB
- BaseCollectionStatsStorage() - Constructor for class org.deeplearning4j.ui.storage.BaseCollectionStatsStorage
-
- BaseCollectionStatsStorage.SessionTypeId - Class in org.deeplearning4j.ui.storage
-
- BaseCollectionStatsStorage.SessionTypeWorkerId - Class in org.deeplearning4j.ui.storage
-
- BaseConstraint - Class in org.deeplearning4j.nn.conf.constraint
-
- BaseConstraint() - Constructor for class org.deeplearning4j.nn.conf.constraint.BaseConstraint
-
- BaseConstraint(Set<String>, int...) - Constructor for class org.deeplearning4j.nn.conf.constraint.BaseConstraint
-
- BaseConvBuilder(int[], int[], int[], int[], int) - Constructor for class org.deeplearning4j.nn.conf.layers.ConvolutionLayer.BaseConvBuilder
-
- BaseConvBuilder(int[], int[], int[], int[]) - Constructor for class org.deeplearning4j.nn.conf.layers.ConvolutionLayer.BaseConvBuilder
-
- BaseConvBuilder(int[], int[], int[], int) - Constructor for class org.deeplearning4j.nn.conf.layers.ConvolutionLayer.BaseConvBuilder
-
- BaseConvBuilder(int[], int[], int[]) - Constructor for class org.deeplearning4j.nn.conf.layers.ConvolutionLayer.BaseConvBuilder
-
- BaseConvBuilder(int[], int[], int) - Constructor for class org.deeplearning4j.nn.conf.layers.ConvolutionLayer.BaseConvBuilder
-
- BaseConvBuilder(int[], int[]) - Constructor for class org.deeplearning4j.nn.conf.layers.ConvolutionLayer.BaseConvBuilder
-
- BaseConvBuilder(int, int...) - Constructor for class org.deeplearning4j.nn.conf.layers.ConvolutionLayer.BaseConvBuilder
-
- BaseConvBuilder(int...) - Constructor for class org.deeplearning4j.nn.conf.layers.ConvolutionLayer.BaseConvBuilder
-
- BaseConvBuilder() - Constructor for class org.deeplearning4j.nn.conf.layers.ConvolutionLayer.BaseConvBuilder
-
- BaseCudnnHelper - Class in org.deeplearning4j.nn.layers
-
Functionality shared by all cuDNN-based helpers.
- BaseCudnnHelper() - Constructor for class org.deeplearning4j.nn.layers.BaseCudnnHelper
-
- BaseCudnnHelper.CudnnContext - Class in org.deeplearning4j.nn.layers
-
- BaseCudnnHelper.CudnnContext.Deallocator - Class in org.deeplearning4j.nn.layers
-
- BaseCudnnHelper.DataCache - Class in org.deeplearning4j.nn.layers
-
- BaseCudnnHelper.TensorArray - Class in org.deeplearning4j.nn.layers
-
- BaseCurve - Class in org.deeplearning4j.eval.curves
-
Abstract class for ROC and Precision recall curves
- BaseCurve() - Constructor for class org.deeplearning4j.eval.curves.BaseCurve
-
- BaseDatasetIterator - Class in org.deeplearning4j.datasets.iterator
-
Baseline implementation includes
control over the data fetcher and some basic
getters for metadata
- BaseDatasetIterator(int, int, BaseDataFetcher) - Constructor for class org.deeplearning4j.datasets.iterator.BaseDatasetIterator
-
- BaseDataSetIterator<T> - Class in org.deeplearning4j.spark.iterator
-
Created by huitseeker on 2/15/17.
- BaseDataSetIterator() - Constructor for class org.deeplearning4j.spark.iterator.BaseDataSetIterator
-
- BaseDoubleFlatMapFunctionAdaptee<T> - Class in org.deeplearning4j.spark.util
-
DoubleFlatMapFunction adapter to hide incompatibilities between Spark 1.x and Spark 2.x
This class should be used instead of direct referral to DoubleFlatMapFunction
- BaseDoubleFlatMapFunctionAdaptee(FlatMapFunctionAdapter<T, Double>) - Constructor for class org.deeplearning4j.spark.util.BaseDoubleFlatMapFunctionAdaptee
-
- BaseEarlyStoppingTrainer<T extends Model> - Class in org.deeplearning4j.earlystopping.trainer
-
Base/abstract class for conducting early stopping training locally (single machine).
Can be used to train a
MultiLayerNetwork or a
ComputationGraph via early stopping
- BaseEarlyStoppingTrainer(EarlyStoppingConfiguration<T>, T, DataSetIterator, MultiDataSetIterator, EarlyStoppingListener<T>) - Constructor for class org.deeplearning4j.earlystopping.trainer.BaseEarlyStoppingTrainer
-
- BaseEvaluation<T extends BaseEvaluation> - Class in org.deeplearning4j.eval
-
- BaseEvaluation() - Constructor for class org.deeplearning4j.eval.BaseEvaluation
-
- BaseEventStats - Class in org.deeplearning4j.spark.stats
-
Created by Alex on 26/06/2016.
- BaseEventStats(long, long) - Constructor for class org.deeplearning4j.spark.stats.BaseEventStats
-
- BaseEventStats(String, String, long, long, long) - Constructor for class org.deeplearning4j.spark.stats.BaseEventStats
-
- BaseFileIterator<T,P> - Class in org.deeplearning4j.datasets.iterator.file
-
Base class for loading DataSet objects from file
- BaseFileIterator(File, int, String...) - Constructor for class org.deeplearning4j.datasets.iterator.file.BaseFileIterator
-
- BaseFileIterator(File[], boolean, Random, int, String...) - Constructor for class org.deeplearning4j.datasets.iterator.file.BaseFileIterator
-
- BaseGraph<V,E> - Class in org.deeplearning4j.graph.api
-
- BaseGraph() - Constructor for class org.deeplearning4j.graph.api.BaseGraph
-
- BaseGraphVertex - Class in org.deeplearning4j.nn.graph.vertex
-
BaseGraphVertex defines a set of common functionality for GraphVertex instances.
- BaseGraphVertex(ComputationGraph, String, int, VertexIndices[], VertexIndices[]) - Constructor for class org.deeplearning4j.nn.graph.vertex.BaseGraphVertex
-
- BaseHistogram - Class in org.deeplearning4j.eval.curves
-
Created by Alex on 06/07/2017.
- BaseHistogram() - Constructor for class org.deeplearning4j.eval.curves.BaseHistogram
-
- BaseIEvaluationScoreCalculator<T extends Model,U extends IEvaluation> - Class in org.deeplearning4j.earlystopping.scorecalc.base
-
Base score function based on an IEvaluation instance.
- BaseIEvaluationScoreCalculator(MultiDataSetIterator) - Constructor for class org.deeplearning4j.earlystopping.scorecalc.base.BaseIEvaluationScoreCalculator
-
- BaseIEvaluationScoreCalculator(DataSetIterator) - Constructor for class org.deeplearning4j.earlystopping.scorecalc.base.BaseIEvaluationScoreCalculator
-
- BaseInputPreProcessor - Class in org.deeplearning4j.nn.conf.preprocessor
-
- BaseInputPreProcessor() - Constructor for class org.deeplearning4j.nn.conf.preprocessor.BaseInputPreProcessor
-
- BaseLabels - Class in org.deeplearning4j.zoo.util
-
Base functionality for helper classes that return label descriptions.
- BaseLabels() - Constructor for class org.deeplearning4j.zoo.util.BaseLabels
-
- BaseLabels(String) - Constructor for class org.deeplearning4j.zoo.util.BaseLabels
-
No need to override anything with this constructor.
- BaseLayer - Class in org.deeplearning4j.nn.conf.layers
-
A neural network layer.
- BaseLayer(BaseLayer.Builder) - Constructor for class org.deeplearning4j.nn.conf.layers.BaseLayer
-
- BaseLayer<LayerConfT extends BaseLayer> - Class in org.deeplearning4j.nn.layers
-
A layer with parameters
- BaseLayer(NeuralNetConfiguration) - Constructor for class org.deeplearning4j.nn.layers.BaseLayer
-
- BaseLayer(NeuralNetConfiguration, INDArray) - Constructor for class org.deeplearning4j.nn.layers.BaseLayer
-
- BaseLayer.Builder<T extends BaseLayer.Builder<T>> - Class in org.deeplearning4j.nn.conf.layers
-
- BaseMLNScoreCalculator - Class in org.deeplearning4j.earlystopping.scorecalc.base
-
Abstract score calculator for MultiLayerNetwonk
- BaseMLNScoreCalculator(DataSetIterator) - Constructor for class org.deeplearning4j.earlystopping.scorecalc.base.BaseMLNScoreCalculator
-
- BaseMultiLayerUpdater<T extends Model> - Class in org.deeplearning4j.nn.updater
-
BaseMultiLayerUpdater - core functionality for applying updaters to MultiLayerNetwork and ComputationGraph.
- BaseMultiLayerUpdater(T) - Constructor for class org.deeplearning4j.nn.updater.BaseMultiLayerUpdater
-
- BaseMultiLayerUpdater(T, INDArray) - Constructor for class org.deeplearning4j.nn.updater.BaseMultiLayerUpdater
-
- BaseNetConfigDeserializer<T> - Class in org.deeplearning4j.nn.conf.serde
-
A custom (abstract) deserializer that handles backward compatibility (currently only for updater refactoring that
happened after 0.8.0).
- BaseNetConfigDeserializer(JsonDeserializer<?>, Class<T>) - Constructor for class org.deeplearning4j.nn.conf.serde.BaseNetConfigDeserializer
-
- BaseOptimizer - Class in org.deeplearning4j.optimize.solvers
-
Base optimizer
- BaseOptimizer(NeuralNetConfiguration, StepFunction, Collection<TrainingListener>, Model) - Constructor for class org.deeplearning4j.optimize.solvers.BaseOptimizer
-
- BaseOptimizer(NeuralNetConfiguration, StepFunction, Collection<TrainingListener>, Collection<TerminationCondition>, Model) - Constructor for class org.deeplearning4j.optimize.solvers.BaseOptimizer
-
- BaseOutputLayer - Class in org.deeplearning4j.nn.conf.layers
-
- BaseOutputLayer(BaseOutputLayer.Builder) - Constructor for class org.deeplearning4j.nn.conf.layers.BaseOutputLayer
-
- BaseOutputLayer<LayerConfT extends BaseOutputLayer> - Class in org.deeplearning4j.nn.layers
-
Output layer with different objective
in co-occurrences for different objectives.
- BaseOutputLayer(NeuralNetConfiguration) - Constructor for class org.deeplearning4j.nn.layers.BaseOutputLayer
-
- BaseOutputLayer(NeuralNetConfiguration, INDArray) - Constructor for class org.deeplearning4j.nn.layers.BaseOutputLayer
-
- BaseOutputLayer.Builder<T extends BaseOutputLayer.Builder<T>> - Class in org.deeplearning4j.nn.conf.layers
-
- BasePairFlatMapFunctionAdaptee<T,K,V> - Class in org.deeplearning4j.spark.util
-
PairFlatMapFunction adapter to hide incompatibilities between Spark 1.x and Spark 2.x
This class should be used instead of direct referral to PairFlatMapFunction
- BasePairFlatMapFunctionAdaptee(FlatMapFunctionAdapter<T, Tuple2<K, V>>) - Constructor for class org.deeplearning4j.spark.util.BasePairFlatMapFunctionAdaptee
-
- BaseParallelDataSetIterator - Class in org.deeplearning4j.datasets.iterator.parallel
-
- BaseParallelDataSetIterator(int) - Constructor for class org.deeplearning4j.datasets.iterator.parallel.BaseParallelDataSetIterator
-
- BasePipeline - Class in org.deeplearning4j
-
Base pipeline class
- BasePipeline() - Constructor for class org.deeplearning4j.BasePipeline
-
- BasePipeline.Builder - Class in org.deeplearning4j
-
- BasePretrainNetwork - Class in org.deeplearning4j.nn.conf.layers
-
- BasePretrainNetwork(BasePretrainNetwork.Builder) - Constructor for class org.deeplearning4j.nn.conf.layers.BasePretrainNetwork
-
- BasePretrainNetwork<LayerConfT extends BasePretrainNetwork> - Class in org.deeplearning4j.nn.layers
-
Baseline class for any Neural Network used
as a layer in a deep network *
- BasePretrainNetwork(NeuralNetConfiguration) - Constructor for class org.deeplearning4j.nn.layers.BasePretrainNetwork
-
- BasePretrainNetwork(NeuralNetConfiguration, INDArray) - Constructor for class org.deeplearning4j.nn.layers.BasePretrainNetwork
-
- BasePretrainNetwork.Builder<T extends BasePretrainNetwork.Builder<T>> - Class in org.deeplearning4j.nn.conf.layers
-
- BaseRecurrentLayer - Class in org.deeplearning4j.nn.conf.layers
-
- BaseRecurrentLayer(BaseRecurrentLayer.Builder) - Constructor for class org.deeplearning4j.nn.conf.layers.BaseRecurrentLayer
-
- BaseRecurrentLayer<LayerConfT extends BaseLayer> - Class in org.deeplearning4j.nn.layers.recurrent
-
- BaseRecurrentLayer(NeuralNetConfiguration) - Constructor for class org.deeplearning4j.nn.layers.recurrent.BaseRecurrentLayer
-
- BaseRecurrentLayer(NeuralNetConfiguration, INDArray) - Constructor for class org.deeplearning4j.nn.layers.recurrent.BaseRecurrentLayer
-
- BaseRecurrentLayer.Builder<T extends BaseRecurrentLayer.Builder<T>> - Class in org.deeplearning4j.nn.conf.layers
-
- BaseS3 - Class in org.deeplearning4j.aws.s3
-
The S3 Credentials works via discovering the credentials
from the system properties (passed in via -D or System wide)
If you invoke the JVM with -Dorg.deeplearning4j.aws.accessKey=YOUR_ACCESS_KEY
and -Dorg.deeplearning4j.aws.accessSecret=YOUR_SECRET_KEY
this will pick up the credentials from there, otherwise it will also attempt to look in
the system environment for the following variables:
AWS_ACCESS_KEY_ID
AWS_SECRET_ACCESS_KEY
- BaseS3() - Constructor for class org.deeplearning4j.aws.s3.BaseS3
-
- BaseS3(File) - Constructor for class org.deeplearning4j.aws.s3.BaseS3
-
- BaseS3(InputStream) - Constructor for class org.deeplearning4j.aws.s3.BaseS3
-
- BaseS3DataSetIterator - Class in org.deeplearning4j.aws.s3.reader
-
baseline data applyTransformToDestination iterator for
- BaseS3DataSetIterator() - Constructor for class org.deeplearning4j.aws.s3.reader.BaseS3DataSetIterator
-
- BaseSameDiffLayer - Class in org.deeplearning4j.nn.conf.layers.samediff
-
A base layer used for implementing Deeplearning4j layers using SameDiff.
- BaseSameDiffLayer(BaseSameDiffLayer.Builder) - Constructor for class org.deeplearning4j.nn.conf.layers.samediff.BaseSameDiffLayer
-
- BaseSameDiffLayer() - Constructor for class org.deeplearning4j.nn.conf.layers.samediff.BaseSameDiffLayer
-
- BaseSameDiffLayer.Builder<T extends BaseSameDiffLayer.Builder<T>> - Class in org.deeplearning4j.nn.conf.layers.samediff
-
- BaseScoreCalculator<T extends Model> - Class in org.deeplearning4j.earlystopping.scorecalc.base
-
- BaseScoreCalculator(DataSetIterator) - Constructor for class org.deeplearning4j.earlystopping.scorecalc.base.BaseScoreCalculator
-
- BaseScoreCalculator(MultiDataSetIterator) - Constructor for class org.deeplearning4j.earlystopping.scorecalc.base.BaseScoreCalculator
-
- BaseSentenceIterator - Class in org.deeplearning4j.text.sentenceiterator
-
Creates a baseline default.
- BaseSentenceIterator(SentencePreProcessor) - Constructor for class org.deeplearning4j.text.sentenceiterator.BaseSentenceIterator
-
- BaseSentenceIterator() - Constructor for class org.deeplearning4j.text.sentenceiterator.BaseSentenceIterator
-
- BaseSparkEarlyStoppingTrainer<T extends Model> - Class in org.deeplearning4j.spark.earlystopping
-
- BaseSparkEarlyStoppingTrainer(JavaSparkContext, EarlyStoppingConfiguration<T>, T, JavaRDD<DataSet>, JavaRDD<MultiDataSet>, EarlyStoppingListener<T>) - Constructor for class org.deeplearning4j.spark.earlystopping.BaseSparkEarlyStoppingTrainer
-
- BaseSparkLearningAlgorithm - Class in org.deeplearning4j.spark.models.sequencevectors.learning.elements
-
- BaseSparkLearningAlgorithm() - Constructor for class org.deeplearning4j.spark.models.sequencevectors.learning.elements.BaseSparkLearningAlgorithm
-
- BaseSparkSequenceLearningAlgorithm - Class in org.deeplearning4j.spark.models.sequencevectors.learning.sequence
-
- BaseSparkSequenceLearningAlgorithm() - Constructor for class org.deeplearning4j.spark.models.sequencevectors.learning.sequence.BaseSparkSequenceLearningAlgorithm
-
- BaseStatsListener - Class in org.deeplearning4j.ui.stats
-
BaseStatsListener: a general purpose listener for collecting and reporting system and model information.
- BaseStatsListener(StatsStorageRouter) - Constructor for class org.deeplearning4j.ui.stats.BaseStatsListener
-
Create a StatsListener with network information collected at every iteration.
- BaseStatsListener(StatsStorageRouter, int) - Constructor for class org.deeplearning4j.ui.stats.BaseStatsListener
-
Create a StatsListener with network information collected every n >= 1 time steps
- BaseStatsListener(StatsStorageRouter, StatsInitializationConfiguration, StatsUpdateConfiguration, String, String) - Constructor for class org.deeplearning4j.ui.stats.BaseStatsListener
-
- BaseSubsamplingBuilder(Subsampling3DLayer.PoolingType, int[], int[]) - Constructor for class org.deeplearning4j.nn.conf.layers.Subsampling3DLayer.BaseSubsamplingBuilder
-
- BaseSubsamplingBuilder(Subsampling3DLayer.PoolingType, int[]) - Constructor for class org.deeplearning4j.nn.conf.layers.Subsampling3DLayer.BaseSubsamplingBuilder
-
- BaseSubsamplingBuilder(Subsampling3DLayer.PoolingType, int[], int[], int[]) - Constructor for class org.deeplearning4j.nn.conf.layers.Subsampling3DLayer.BaseSubsamplingBuilder
-
- BaseSubsamplingBuilder(PoolingType, int[]) - Constructor for class org.deeplearning4j.nn.conf.layers.Subsampling3DLayer.BaseSubsamplingBuilder
-
- BaseSubsamplingBuilder(PoolingType, int[], int[], int[]) - Constructor for class org.deeplearning4j.nn.conf.layers.Subsampling3DLayer.BaseSubsamplingBuilder
-
- BaseSubsamplingBuilder(int[], int[], int[]) - Constructor for class org.deeplearning4j.nn.conf.layers.Subsampling3DLayer.BaseSubsamplingBuilder
-
- BaseSubsamplingBuilder(int[], int[]) - Constructor for class org.deeplearning4j.nn.conf.layers.Subsampling3DLayer.BaseSubsamplingBuilder
-
- BaseSubsamplingBuilder(int...) - Constructor for class org.deeplearning4j.nn.conf.layers.Subsampling3DLayer.BaseSubsamplingBuilder
-
- BaseSubsamplingBuilder(Subsampling3DLayer.PoolingType) - Constructor for class org.deeplearning4j.nn.conf.layers.Subsampling3DLayer.BaseSubsamplingBuilder
-
- BaseSubsamplingBuilder(PoolingType) - Constructor for class org.deeplearning4j.nn.conf.layers.Subsampling3DLayer.BaseSubsamplingBuilder
-
- BaseSubsamplingBuilder(SubsamplingLayer.PoolingType, int[], int[]) - Constructor for class org.deeplearning4j.nn.conf.layers.SubsamplingLayer.BaseSubsamplingBuilder
-
- BaseSubsamplingBuilder(SubsamplingLayer.PoolingType, int[]) - Constructor for class org.deeplearning4j.nn.conf.layers.SubsamplingLayer.BaseSubsamplingBuilder
-
- BaseSubsamplingBuilder(SubsamplingLayer.PoolingType, int[], int[], int[]) - Constructor for class org.deeplearning4j.nn.conf.layers.SubsamplingLayer.BaseSubsamplingBuilder
-
- BaseSubsamplingBuilder(PoolingType, int[]) - Constructor for class org.deeplearning4j.nn.conf.layers.SubsamplingLayer.BaseSubsamplingBuilder
-
- BaseSubsamplingBuilder(PoolingType, int[], int[], int[]) - Constructor for class org.deeplearning4j.nn.conf.layers.SubsamplingLayer.BaseSubsamplingBuilder
-
- BaseSubsamplingBuilder(int[], int[], int[]) - Constructor for class org.deeplearning4j.nn.conf.layers.SubsamplingLayer.BaseSubsamplingBuilder
-
- BaseSubsamplingBuilder(int[], int[]) - Constructor for class org.deeplearning4j.nn.conf.layers.SubsamplingLayer.BaseSubsamplingBuilder
-
- BaseSubsamplingBuilder(int...) - Constructor for class org.deeplearning4j.nn.conf.layers.SubsamplingLayer.BaseSubsamplingBuilder
-
- BaseSubsamplingBuilder(SubsamplingLayer.PoolingType) - Constructor for class org.deeplearning4j.nn.conf.layers.SubsamplingLayer.BaseSubsamplingBuilder
-
- BaseSubsamplingBuilder(PoolingType) - Constructor for class org.deeplearning4j.nn.conf.layers.SubsamplingLayer.BaseSubsamplingBuilder
-
- BaseTextVectorizer - Class in org.deeplearning4j.bagofwords.vectorizer
-
- BaseTextVectorizer() - Constructor for class org.deeplearning4j.bagofwords.vectorizer.BaseTextVectorizer
-
- BaseTokenizerFunction - Class in org.deeplearning4j.spark.models.sequencevectors.functions
-
- BaseTokenizerFunction(Broadcast<VectorsConfiguration>) - Constructor for class org.deeplearning4j.spark.models.sequencevectors.functions.BaseTokenizerFunction
-
- BaseTrainingListener - Class in org.deeplearning4j.optimize.api
-
A no-op implementation of a
TrainingListener to be used as a starting point for custom training callbacks.
- BaseTrainingListener() - Constructor for class org.deeplearning4j.optimize.api.BaseTrainingListener
-
- BaseTrainingMaster<R extends TrainingResult,W extends TrainingWorker<R>> - Class in org.deeplearning4j.spark.impl.paramavg
-
- BaseTrainingMaster() - Constructor for class org.deeplearning4j.spark.impl.paramavg.BaseTrainingMaster
-
- BaseTrainingResult - Class in org.deeplearning4j.spark.impl.paramavg
-
- BaseTrainingResult() - Constructor for class org.deeplearning4j.spark.impl.paramavg.BaseTrainingResult
-
- BaseTrainingWorker<R extends TrainingResult> - Class in org.deeplearning4j.spark.impl.paramavg
-
- BaseTrainingWorker() - Constructor for class org.deeplearning4j.spark.impl.paramavg.BaseTrainingWorker
-
- BaseUpsamplingLayer - Class in org.deeplearning4j.nn.conf.layers
-
Upsampling base layer
- BaseUpsamplingLayer(BaseUpsamplingLayer.UpsamplingBuilder) - Constructor for class org.deeplearning4j.nn.conf.layers.BaseUpsamplingLayer
-
- BaseUpsamplingLayer.UpsamplingBuilder<T extends BaseUpsamplingLayer.UpsamplingBuilder<T>> - Class in org.deeplearning4j.nn.conf.layers
-
- BaseVaeReconstructionProbWithKeyFunctionAdapter<K> - Class in org.deeplearning4j.spark.impl.common.score
-
Function to calculate the scores (reconstruction probability or log probability) for a variational autoencoder.
Note that scoring is batched for computational efficiency.
- BaseVaeReconstructionProbWithKeyFunctionAdapter(Broadcast<INDArray>, Broadcast<String>, boolean, int, int) - Constructor for class org.deeplearning4j.spark.impl.common.score.BaseVaeReconstructionProbWithKeyFunctionAdapter
-
- BaseVaeScoreWithKeyFunctionAdapter<K> - Class in org.deeplearning4j.spark.impl.common.score
-
Function to calculate the scores (reconstruction probability, reconstruction error) for a variational autoencoder.
Note that scoring is batched for computational efficiency.
- BaseVaeScoreWithKeyFunctionAdapter(Broadcast<INDArray>, Broadcast<String>, int) - Constructor for class org.deeplearning4j.spark.impl.common.score.BaseVaeScoreWithKeyFunctionAdapter
-
- BaseWrapperLayer - Class in org.deeplearning4j.nn.conf.layers.wrapper
-
Base wrapper layer: the idea is to pass through all methods to the underlying layer, and selectively override
them as required.
- BaseWrapperLayer() - Constructor for class org.deeplearning4j.nn.conf.layers.wrapper.BaseWrapperLayer
-
- BaseWrapperLayer(Layer) - Constructor for class org.deeplearning4j.nn.conf.layers.wrapper.BaseWrapperLayer
-
- BaseWrapperLayer - Class in org.deeplearning4j.nn.layers.wrapper
-
Abstract wrapper layer.
- BaseWrapperLayer(Layer) - Constructor for class org.deeplearning4j.nn.layers.wrapper.BaseWrapperLayer
-
- BaseWrapperVertex - Class in org.deeplearning4j.nn.graph.vertex
-
A base class for wrapper vertices: i.e., those vertices that have another vertex inside.
- BaseWrapperVertex(GraphVertex) - Constructor for class org.deeplearning4j.nn.graph.vertex.BaseWrapperVertex
-
- BasicGradientsAccumulator - Class in org.deeplearning4j.optimize.solvers.accumulation
-
This class provides accumulation for gradients for both input (i.e.
- BasicGradientsAccumulator(int) - Constructor for class org.deeplearning4j.optimize.solvers.accumulation.BasicGradientsAccumulator
-
Creates new GradientsAccumulator with starting threshold of 1e-3
- BasicGradientsAccumulator(int, MessageHandler) - Constructor for class org.deeplearning4j.optimize.solvers.accumulation.BasicGradientsAccumulator
-
Creates new GradientsAccumulator with custom starting threshold
- BasicInferenceObservable - Class in org.deeplearning4j.parallelism.inference.observers
-
This class holds reference input, and implements basic use case: SEQUENTIAL inference
- BasicInferenceObservable(INDArray...) - Constructor for class org.deeplearning4j.parallelism.inference.observers.BasicInferenceObservable
-
- BasicInferenceObservable(INDArray[], INDArray[]) - Constructor for class org.deeplearning4j.parallelism.inference.observers.BasicInferenceObservable
-
- BasicInferenceObserver - Class in org.deeplearning4j.parallelism.inference.observers
-
Simple Observer implementation for
sequential inference
- BasicInferenceObserver() - Constructor for class org.deeplearning4j.parallelism.inference.observers.BasicInferenceObserver
-
- BasicLabelAwareIterator - Class in org.deeplearning4j.text.documentiterator
-
This is simple class, for building Sentence-Label pairs for ParagraphVectors/Doc2Vec.
- BasicLabelAwareIterator.Builder - Class in org.deeplearning4j.text.documentiterator
-
- BasicLineIterator - Class in org.deeplearning4j.text.sentenceiterator
-
Primitive single-line iterator, without any options involved.
- BasicLineIterator(File) - Constructor for class org.deeplearning4j.text.sentenceiterator.BasicLineIterator
-
- BasicLineIterator(InputStream) - Constructor for class org.deeplearning4j.text.sentenceiterator.BasicLineIterator
-
- BasicLineIterator(String) - Constructor for class org.deeplearning4j.text.sentenceiterator.BasicLineIterator
-
- BasicModelUtils<T extends SequenceElement> - Class in org.deeplearning4j.models.embeddings.reader.impl
-
Basic implementation for ModelUtils interface, suited for standalone use.
- BasicModelUtils() - Constructor for class org.deeplearning4j.models.embeddings.reader.impl.BasicModelUtils
-
- BasicModelUtils.ArrayComparator - Class in org.deeplearning4j.models.embeddings.reader.impl
-
- BasicModelUtils.SimilarityComparator - Class in org.deeplearning4j.models.embeddings.reader.impl
-
- BasicModelUtils.WordSimilarity - Class in org.deeplearning4j.models.embeddings.reader.impl
-
- BasicResultSetIterator - Class in org.deeplearning4j.text.sentenceiterator
-
Primitive iterator over a SQL ResultSet
Please note: for reset functionality, the underlying JDBC ResultSet must not be of TYPE_FORWARD_ONLY
To achieve this using postgres you can make your query using: connection.prepareStatement(sql,ResultSet.TYPE_SCROLL_INSENSITIVE,ResultSet.CONCUR_READ_ONLY);
This class is designed in a similar fashion to org.deeplearning4j.text.sentenceiterator.BasicLineIterator
- BasicResultSetIterator(ResultSet, String) - Constructor for class org.deeplearning4j.text.sentenceiterator.BasicResultSetIterator
-
- BasicTransformerIterator - Class in org.deeplearning4j.models.sequencevectors.transformers.impl.iterables
-
- BasicTransformerIterator(LabelAwareIterator, SentenceTransformer) - Constructor for class org.deeplearning4j.models.sequencevectors.transformers.impl.iterables.BasicTransformerIterator
-
- batch() - Method in class org.deeplearning4j.datasets.datavec.RecordReaderDataSetIterator
-
- batch() - Method in class org.deeplearning4j.datasets.datavec.SequenceRecordReaderDataSetIterator
-
- batch() - Method in class org.deeplearning4j.datasets.iterator.AbstractDataSetIterator
-
Batch size
- batch() - Method in class org.deeplearning4j.datasets.iterator.AsyncDataSetIterator
-
Batch size
- batch() - Method in class org.deeplearning4j.datasets.iterator.AsyncShieldDataSetIterator
-
Batch size
- batch - Variable in class org.deeplearning4j.datasets.iterator.BaseDatasetIterator
-
- batch() - Method in class org.deeplearning4j.datasets.iterator.BaseDatasetIterator
-
- batch() - Method in class org.deeplearning4j.datasets.iterator.EarlyTerminationDataSetIterator
-
- batch() - Method in class org.deeplearning4j.datasets.iterator.ExistingDataSetIterator
-
- batch() - Method in class org.deeplearning4j.datasets.iterator.file.FileDataSetIterator
-
- batch() - Method in class org.deeplearning4j.datasets.iterator.FileSplitDataSetIterator
-
- batch() - Method in class org.deeplearning4j.datasets.iterator.impl.BenchmarkDataSetIterator
-
- batch - Variable in class org.deeplearning4j.datasets.iterator.impl.EmnistDataSetIterator
-
- batch() - Method in class org.deeplearning4j.datasets.iterator.impl.ListDataSetIterator
-
- batch() - Method in class org.deeplearning4j.datasets.iterator.IteratorDataSetIterator
-
- batch() - Method in class org.deeplearning4j.datasets.iterator.MultiDataSetWrapperIterator
-
- batch - Variable in class org.deeplearning4j.datasets.iterator.MultipleEpochsIterator
-
Deprecated.
- batch() - Method in class org.deeplearning4j.datasets.iterator.MultipleEpochsIterator
-
Deprecated.
Batch size
- batch() - Method in class org.deeplearning4j.datasets.iterator.parallel.BaseParallelDataSetIterator
-
- batch() - Method in class org.deeplearning4j.datasets.iterator.ReconstructionDataSetIterator
-
Batch size
- batch() - Method in class org.deeplearning4j.datasets.iterator.SamplingDataSetIterator
-
- batch() - Method in class org.deeplearning4j.datasets.iterator.WorkspacesShieldDataSetIterator
-
- batch() - Method in class org.deeplearning4j.datasets.test.TestDataSetIterator
-
- batch() - Method in class org.deeplearning4j.iterator.CnnSentenceDataSetIterator
-
- batch() - Method in class org.deeplearning4j.models.word2vec.iterator.Word2VecDataSetIterator
-
- batch - Variable in class org.deeplearning4j.spark.iterator.BaseDataSetIterator
-
- batch() - Method in class org.deeplearning4j.spark.iterator.BaseDataSetIterator
-
- batch() - Method in class org.deeplearning4j.spark.parameterserver.iterators.VirtualDataSetIterator
-
- BatchAndExportDataSetsFunction - Class in org.deeplearning4j.spark.data
-
Function used with RDD<DataSet>.mapPartitionsWithIndex.
- BatchAndExportDataSetsFunction(int, String) - Constructor for class org.deeplearning4j.spark.data.BatchAndExportDataSetsFunction
-
- BatchAndExportMultiDataSetsFunction - Class in org.deeplearning4j.spark.data
-
Function used with RDD<MultiDataSet>.mapPartitionsWithIndex.
- BatchAndExportMultiDataSetsFunction(int, String) - Constructor for class org.deeplearning4j.spark.data.BatchAndExportMultiDataSetsFunction
-
- BatchDataSetsFunction - Class in org.deeplearning4j.spark.data
-
Function used to batch DataSet objects together.
- BatchDataSetsFunction(int) - Constructor for class org.deeplearning4j.spark.data.BatchDataSetsFunction
-
- batchedDS - Variable in class org.deeplearning4j.datasets.iterator.MultipleEpochsIterator
-
Deprecated.
- BatchedInferenceObservable - Class in org.deeplearning4j.parallelism.inference.observers
-
This class holds reference input, and implements second use case: BATCHED inference
- BatchedInferenceObservable() - Constructor for class org.deeplearning4j.parallelism.inference.observers.BatchedInferenceObservable
-
- batches - Variable in class org.deeplearning4j.models.embeddings.learning.impl.elements.CBOW
-
- batches - Variable in class org.deeplearning4j.models.embeddings.learning.impl.elements.SkipGram
-
- batchesSupported() - Method in class org.deeplearning4j.spark.datavec.iterator.SparkSourceDummyReader
-
- batchIter(int) - Method in interface org.deeplearning4j.text.invertedindex.InvertedIndex
-
Iterate over batches
- batchLimit(int) - Method in class org.deeplearning4j.parallelism.ParallelInference.Builder
-
This method defines, how many input samples can
be batched within given time frame.
- batchNorm(int, int) - Static method in class org.deeplearning4j.zoo.model.helper.FaceNetHelper
-
- BatchNormalization - Class in org.deeplearning4j.nn.conf.layers
-
Batch normalization configuration
- BatchNormalization - Class in org.deeplearning4j.nn.layers.normalization
-
Batch normalization layer.
- BatchNormalization(NeuralNetConfiguration) - Constructor for class org.deeplearning4j.nn.layers.normalization.BatchNormalization
-
- BatchNormalization.Builder - Class in org.deeplearning4j.nn.conf.layers
-
- BatchNormalizationHelper - Interface in org.deeplearning4j.nn.layers.normalization
-
Helper for the batch normalization layer.
- BatchNormalizationParamInitializer - Class in org.deeplearning4j.nn.params
-
Batch normalization variable init
- BatchNormalizationParamInitializer() - Constructor for class org.deeplearning4j.nn.params.BatchNormalizationParamInitializer
-
- batchNormMode - Variable in class org.deeplearning4j.nn.layers.normalization.CudnnBatchNormalizationHelper
-
- batchNum - Variable in class org.deeplearning4j.datasets.datavec.RecordReaderDataSetIterator
-
- BatchRecord - Class in org.deeplearning4j.nearestneighbor.model
-
Created by agibsonccc on 1/21/17.
- BatchRecord() - Constructor for class org.deeplearning4j.nearestneighbor.model.BatchRecord
-
- batchSize - Variable in class org.deeplearning4j.bagofwords.vectorizer.Builder
-
Deprecated.
- batchSize(int) - Method in class org.deeplearning4j.bagofwords.vectorizer.Builder
-
Deprecated.
- batchSize - Variable in class org.deeplearning4j.datasets.datavec.RecordReaderDataSetIterator
-
- batchSize - Variable in class org.deeplearning4j.datasets.datavec.RecordReaderDataSetIterator.Builder
-
- batchSize - Variable in class org.deeplearning4j.datasets.iterator.file.BaseFileIterator
-
- batchSize - Variable in class org.deeplearning4j.models.embeddings.learning.impl.elements.GloVe
-
- batchSize - Variable in class org.deeplearning4j.models.embeddings.learning.impl.elements.GloVe.Builder
-
- batchSize(int) - Method in class org.deeplearning4j.models.embeddings.learning.impl.elements.GloVe.Builder
-
This parameter specifies batch size for each thread.
- batchSize - Variable in class org.deeplearning4j.models.embeddings.wordvectors.WordVectorsImpl
-
- batchSize(int) - Method in class org.deeplearning4j.models.glove.Glove.Builder
-
Specifies minibatch size for training process.
- batchSize(int) - Method in class org.deeplearning4j.models.paragraphvectors.ParagraphVectors.Builder
-
This method defines mini-batch size
- batchSize - Variable in class org.deeplearning4j.models.sequencevectors.SequenceVectors.Builder
-
- batchSize(int) - Method in class org.deeplearning4j.models.sequencevectors.SequenceVectors.Builder
-
This method defines batchSize option, viable only if iterations > 1
- batchSize(int) - Method in class org.deeplearning4j.models.word2vec.Word2Vec.Builder
-
This method defines mini-batch size
- batchSize() - Method in interface org.deeplearning4j.nn.api.Model
-
The current inputs batch size
- batchSize() - Method in class org.deeplearning4j.nn.graph.ComputationGraph
-
- batchSize() - Method in class org.deeplearning4j.nn.layers.AbstractLayer
-
- batchSize() - Method in class org.deeplearning4j.nn.layers.recurrent.BidirectionalLayer
-
- batchSize() - Method in class org.deeplearning4j.nn.layers.variational.VariationalAutoencoder
-
- batchSize() - Method in class org.deeplearning4j.nn.layers.wrapper.BaseWrapperLayer
-
- batchSize() - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
-
- batchSize() - Method in interface org.deeplearning4j.optimize.api.ConvexOptimizer
-
The batch size for the optimizer
- batchSize() - Method in class org.deeplearning4j.optimize.solvers.BaseOptimizer
-
- batchSize() - Method in class org.deeplearning4j.plot.BarnesHutTsne
-
- batchSize - Variable in class org.deeplearning4j.spark.datavec.DataVecDataSetFunction
-
- batchSize - Variable in class org.deeplearning4j.spark.models.embeddings.word2vec.Word2Vec.Builder
-
- batchSize(int) - Method in class org.deeplearning4j.spark.models.embeddings.word2vec.Word2Vec.Builder
-
Specifies the size of mini-batch, used in single iteration during training
- batchSize - Variable in class org.deeplearning4j.spark.parameterserver.training.SharedTrainingMaster.Builder
-
- batchSize() - Method in interface org.deeplearning4j.text.invertedindex.InvertedIndex
-
For word vectors, this is the batch size for which to train on
- batchSizePerWorker - Variable in class org.deeplearning4j.spark.api.WorkerConfiguration
-
- batchSizePerWorker - Variable in class org.deeplearning4j.spark.impl.paramavg.BaseTrainingMaster
-
- batchSizePerWorker - Variable in class org.deeplearning4j.spark.impl.paramavg.ParameterAveragingTrainingMaster.Builder
-
- batchSizePerWorker(int) - Method in class org.deeplearning4j.spark.impl.paramavg.ParameterAveragingTrainingMaster.Builder
-
Batch size (in number of examples) per worker, for each fit(DataSet) call.
- batchSizePerWorker(int) - Method in class org.deeplearning4j.spark.parameterserver.training.SharedTrainingMaster.Builder
-
Batch size value, used for repartition purposes
- beforeProcessor - Variable in class org.deeplearning4j.streaming.routes.DL4jServeRouteBuilder
-
- begin(String) - Static method in class com.atilika.kuromoji.compile.ProgressLog
-
- BEGIN - Static variable in class org.ansj.app.crf.Config
-
- BEGIN - Static variable in class org.ansj.domain.AnsjItem
-
- begin - Variable in class org.ansj.domain.PersonNatureAttr
-
- BEGIN - Static variable in class org.ansj.domain.TermNature
-
- BEGIN - Static variable in class org.ansj.domain.TermNatures
-
- BenchmarkDataSetIterator - Class in org.deeplearning4j.datasets.iterator.impl
-
Dataset iterator for simulated inputs, or input derived from a DataSet example.
- BenchmarkDataSetIterator(int[], int, int) - Constructor for class org.deeplearning4j.datasets.iterator.impl.BenchmarkDataSetIterator
-
- BenchmarkDataSetIterator(int[], int, int, int, int) - Constructor for class org.deeplearning4j.datasets.iterator.impl.BenchmarkDataSetIterator
-
- BenchmarkDataSetIterator(DataSet, int) - Constructor for class org.deeplearning4j.datasets.iterator.impl.BenchmarkDataSetIterator
-
- BenchmarkMultiDataSetIterator - Class in org.deeplearning4j.datasets.iterator.impl
-
MultiDataset iterator for simulated inputs, or input derived from a MultiDataSet example.
- BenchmarkMultiDataSetIterator(int[][], int[], int) - Constructor for class org.deeplearning4j.datasets.iterator.impl.BenchmarkMultiDataSetIterator
-
- BenchmarkMultiDataSetIterator(MultiDataSet, int) - Constructor for class org.deeplearning4j.datasets.iterator.impl.BenchmarkMultiDataSetIterator
-
- BernoulliReconstructionDistribution - Class in org.deeplearning4j.nn.conf.layers.variational
-
Bernoulli reconstruction distribution for variational autoencoder.
Outputs are modelled by a Bernoulli distribution - i.e., the Bernoulli distribution should be used for binary data (all
values 0 or 1); the VAE models the probability of the output being 0 or 1.
Consequently, the sigmoid activation function should be used to bound activations to the range of 0 to 1.
- BernoulliReconstructionDistribution() - Constructor for class org.deeplearning4j.nn.conf.layers.variational.BernoulliReconstructionDistribution
-
Create a BernoulliReconstructionDistribution with the default Sigmoid activation function
- BernoulliReconstructionDistribution(String) - Constructor for class org.deeplearning4j.nn.conf.layers.variational.BernoulliReconstructionDistribution
-
- BernoulliReconstructionDistribution(Activation) - Constructor for class org.deeplearning4j.nn.conf.layers.variational.BernoulliReconstructionDistribution
-
- BernoulliReconstructionDistribution(IActivation) - Constructor for class org.deeplearning4j.nn.conf.layers.variational.BernoulliReconstructionDistribution
-
- bernoullis(double, double, double) - Static method in class org.deeplearning4j.clustering.util.MathUtils
-
This will return the bernoulli trial for the given event.
- BestScoreEpochTerminationCondition - Class in org.deeplearning4j.earlystopping.termination
-
Created by Sadat Anwar on 3/26/16.
- BestScoreEpochTerminationCondition(double) - Constructor for class org.deeplearning4j.earlystopping.termination.BestScoreEpochTerminationCondition
-
- BestScoreEpochTerminationCondition(double, boolean) - Constructor for class org.deeplearning4j.earlystopping.termination.BestScoreEpochTerminationCondition
-
- beta - Variable in class org.deeplearning4j.nn.conf.layers.BatchNormalization
-
- beta - Variable in class org.deeplearning4j.nn.conf.layers.BatchNormalization.Builder
-
- beta(double) - Method in class org.deeplearning4j.nn.conf.layers.BatchNormalization.Builder
-
- beta - Variable in class org.deeplearning4j.nn.conf.layers.LocalResponseNormalization
-
- beta(double) - Method in class org.deeplearning4j.nn.conf.layers.LocalResponseNormalization.Builder
-
Scaling constant beta.
- beta - Variable in class org.deeplearning4j.nn.layers.BaseCudnnHelper
-
- BETA - Static variable in class org.deeplearning4j.nn.params.BatchNormalizationParamInitializer
-
- betaConstraints - Variable in class org.deeplearning4j.nn.conf.layers.BatchNormalization.Builder
-
- BIAS_KEY - Static variable in class org.deeplearning4j.nn.params.CenterLossParamInitializer
-
- BIAS_KEY - Static variable in class org.deeplearning4j.nn.params.Convolution3DParamInitializer
-
- BIAS_KEY - Static variable in class org.deeplearning4j.nn.params.ConvolutionParamInitializer
-
- BIAS_KEY - Static variable in class org.deeplearning4j.nn.params.DefaultParamInitializer
-
- BIAS_KEY - Static variable in class org.deeplearning4j.nn.params.DepthwiseConvolutionParamInitializer
-
- BIAS_KEY - Static variable in class org.deeplearning4j.nn.params.GravesLSTMParamInitializer
-
- BIAS_KEY - Static variable in class org.deeplearning4j.nn.params.LSTMParamInitializer
-
- BIAS_KEY - Static variable in class org.deeplearning4j.nn.params.SeparableConvolutionParamInitializer
-
- BIAS_KEY - Static variable in class org.deeplearning4j.nn.params.SimpleRnnParamInitializer
-
- BIAS_KEY_BACKWARDS - Static variable in class org.deeplearning4j.nn.params.GravesBidirectionalLSTMParamInitializer
-
- BIAS_KEY_FORWARDS - Static variable in class org.deeplearning4j.nn.params.GravesBidirectionalLSTMParamInitializer
-
- BIAS_KEY_SUFFIX - Static variable in class org.deeplearning4j.nn.params.VariationalAutoencoderParamInitializer
-
- biasConstraints - Variable in class org.deeplearning4j.nn.conf.layers.Layer.Builder
-
- biasConstraints - Variable in class org.deeplearning4j.nn.conf.NeuralNetConfiguration.Builder
-
- biasInit - Variable in class org.deeplearning4j.nn.conf.layers.BaseLayer
-
- biasInit - Variable in class org.deeplearning4j.nn.conf.layers.BaseLayer.Builder
-
- biasInit(double) - Method in class org.deeplearning4j.nn.conf.layers.BaseLayer.Builder
-
Bias initialization value, for layers with biases.
- biasInit - Variable in class org.deeplearning4j.nn.conf.NeuralNetConfiguration.Builder
-
- biasInit(double) - Method in class org.deeplearning4j.nn.conf.NeuralNetConfiguration.Builder
-
Constant for bias initialization.
- biasInit - Variable in class org.deeplearning4j.nn.transferlearning.FineTuneConfiguration
-
- biasInit(double) - Method in class org.deeplearning4j.nn.transferlearning.FineTuneConfiguration.Builder
-
Constant for bias initialization.
- biasKeys(Layer) - Method in interface org.deeplearning4j.nn.api.ParamInitializer
-
Bias parameter keys given the layer configuration
- biasKeys(Layer) - Method in class org.deeplearning4j.nn.layers.ocnn.OCNNParamInitializer
-
- biasKeys(Layer) - Method in class org.deeplearning4j.nn.params.BatchNormalizationParamInitializer
-
- biasKeys(Layer) - Method in class org.deeplearning4j.nn.params.BidirectionalParamInitializer
-
- biasKeys(Layer) - Method in class org.deeplearning4j.nn.params.ConvolutionParamInitializer
-
- biasKeys(Layer) - Method in class org.deeplearning4j.nn.params.DefaultParamInitializer
-
- biasKeys(Layer) - Method in class org.deeplearning4j.nn.params.DepthwiseConvolutionParamInitializer
-
- biasKeys(Layer) - Method in class org.deeplearning4j.nn.params.EmptyParamInitializer
-
- biasKeys(Layer) - Method in class org.deeplearning4j.nn.params.FrozenLayerParamInitializer
-
- biasKeys(Layer) - Method in class org.deeplearning4j.nn.params.FrozenLayerWithBackpropParamInitializer
-
- biasKeys(Layer) - Method in class org.deeplearning4j.nn.params.GravesBidirectionalLSTMParamInitializer
-
- biasKeys(Layer) - Method in class org.deeplearning4j.nn.params.GravesLSTMParamInitializer
-
- biasKeys(Layer) - Method in class org.deeplearning4j.nn.params.LSTMParamInitializer
-
- biasKeys(Layer) - Method in class org.deeplearning4j.nn.params.SameDiffParamInitializer
-
- biasKeys(Layer) - Method in class org.deeplearning4j.nn.params.SeparableConvolutionParamInitializer
-
- biasKeys(Layer) - Method in class org.deeplearning4j.nn.params.SimpleRnnParamInitializer
-
- biasKeys(Layer) - Method in class org.deeplearning4j.nn.params.VariationalAutoencoderParamInitializer
-
- biasKeys(Layer) - Method in class org.deeplearning4j.nn.params.WrapperLayerParamInitializer
-
- biasUpdater - Variable in class org.deeplearning4j.nn.conf.layers.BaseLayer
-
- biasUpdater - Variable in class org.deeplearning4j.nn.conf.layers.BaseLayer.Builder
-
- biasUpdater(IUpdater) - Method in class org.deeplearning4j.nn.conf.layers.BaseLayer.Builder
-
Gradient updater configuration, for the biases only.
- biasUpdater - Variable in class org.deeplearning4j.nn.conf.layers.samediff.AbstractSameDiffLayer
-
- biasUpdater - Variable in class org.deeplearning4j.nn.conf.layers.samediff.AbstractSameDiffLayer.Builder
-
- biasUpdater(IUpdater) - Method in class org.deeplearning4j.nn.conf.layers.samediff.AbstractSameDiffLayer.Builder
-
Gradient updater configuration, for the biases only.
- biasUpdater - Variable in class org.deeplearning4j.nn.conf.NeuralNetConfiguration.Builder
-
- biasUpdater(IUpdater) - Method in class org.deeplearning4j.nn.conf.NeuralNetConfiguration.Builder
-
Gradient updater configuration, for the biases only.
- biasUpdater - Variable in class org.deeplearning4j.nn.transferlearning.FineTuneConfiguration
-
- biasUpdater(IUpdater) - Method in class org.deeplearning4j.nn.transferlearning.FineTuneConfiguration.Builder
-
Gradient updater configuration, for the biases only.
- Bidirectional - Class in org.deeplearning4j.nn.conf.layers.recurrent
-
Bidirectional is a "wrapper" layer: it wraps any uni-directional RNN layer to make it bidirectional.
Note that multiple different modes are supported - these specify how the activations should be combined from
the forward and backward RNN networks.
- Bidirectional(Layer) - Constructor for class org.deeplearning4j.nn.conf.layers.recurrent.Bidirectional
-
Create a Bidirectional wrapper, with the default Mode (CONCAT) for the specified layer
- Bidirectional(Bidirectional.Mode, Layer) - Constructor for class org.deeplearning4j.nn.conf.layers.recurrent.Bidirectional
-
Create a Bidirectional wrapper for the specified layer
- BIDIRECTIONAL - Static variable in class org.deeplearning4j.nn.layers.recurrent.CudnnLSTMHelper
-
- Bidirectional.Builder - Class in org.deeplearning4j.nn.conf.layers.recurrent
-
- Bidirectional.Mode - Enum in org.deeplearning4j.nn.conf.layers.recurrent
-
This Mode enumeration defines how the activations for the forward and backward networks should be combined.
ADD: out = forward + backward (elementwise addition)
MUL: out = forward * backward (elementwise multiplication)
AVERAGE: out = 0.5 * (forward + backward)
CONCAT: Concatenate the activations.
Where 'forward' is the activations for the forward RNN, and 'backward' is the activations for the backward RNN.
- BidirectionalLayer - Class in org.deeplearning4j.nn.layers.recurrent
-
Bidirectional is a "wrapper" layer: it wraps any uni-directional RNN layer to make it bidirectional.
Note that multiple different modes are supported - these specify how the activations should be combined from
the forward and backward RNN networks.
- BidirectionalLayer(NeuralNetConfiguration, RecurrentLayer, RecurrentLayer) - Constructor for class org.deeplearning4j.nn.layers.recurrent.BidirectionalLayer
-
- BidirectionalParamInitializer - Class in org.deeplearning4j.nn.params
-
Parameter initializer for bidirectional wrapper layer
- BidirectionalParamInitializer(Bidirectional) - Constructor for class org.deeplearning4j.nn.params.BidirectionalParamInitializer
-
- bigramEntryMap - Variable in class org.ansj.domain.AnsjItem
-
- binarize - Variable in class org.deeplearning4j.datasets.fetchers.MnistDataFetcher
-
- BinarizeTreeTransformer - Class in org.deeplearning4j.text.corpora.treeparser
-
Binarizes trees.
- BinarizeTreeTransformer() - Constructor for class org.deeplearning4j.text.corpora.treeparser.BinarizeTreeTransformer
-
- BinaryClassificationResult - Class in org.deeplearning4j.nn.simple.binary
-
Created by agibsonccc on 4/28/17.
- BinaryClassificationResult() - Constructor for class org.deeplearning4j.nn.simple.binary.BinaryClassificationResult
-
- BinaryCoOccurrenceReader<T extends SequenceElement> - Class in org.deeplearning4j.models.glove.count
-
Binary implementation of CoOccurenceReader interface, used to provide off-memory storage for cooccurrence maps generated for GloVe
- BinaryCoOccurrenceReader(File, VocabCache<T>, CountMap<T>) - Constructor for class org.deeplearning4j.models.glove.count.BinaryCoOccurrenceReader
-
- BinaryCoOccurrenceWriter<T extends SequenceElement> - Class in org.deeplearning4j.models.glove.count
-
- BinaryCoOccurrenceWriter(File) - Constructor for class org.deeplearning4j.models.glove.count.BinaryCoOccurrenceWriter
-
- binaryDecisionThreshold - Variable in class org.deeplearning4j.eval.Evaluation
-
- binaryPositiveClass - Variable in class org.deeplearning4j.eval.Evaluation
-
- BinaryReader(File) - Constructor for class org.deeplearning4j.models.embeddings.loader.WordVectorSerializer.BinaryReader
-
- BinaryTree - Interface in org.deeplearning4j.graph.models
-
Binary tree interface, used in DeepWalk
- BinaryTree - Interface in org.deeplearning4j.models.sequencevectors.graph.huffman
-
Binary tree interface, used in DeepWalk
- binCount() - Method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder.PerParameterStatsDecoder.HistogramsDecoder.HistogramCountsDecoder
-
- binCount(long) - Method in class org.deeplearning4j.ui.stats.sbe.UpdateEncoder.PerParameterStatsEncoder.HistogramsEncoder.HistogramCountsEncoder
-
- binCountId() - Static method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder.PerParameterStatsDecoder.HistogramsDecoder.HistogramCountsDecoder
-
- binCountMaxValue() - Static method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder.PerParameterStatsDecoder.HistogramsDecoder.HistogramCountsDecoder
-
- binCountMaxValue() - Static method in class org.deeplearning4j.ui.stats.sbe.UpdateEncoder.PerParameterStatsEncoder.HistogramsEncoder.HistogramCountsEncoder
-
- binCountMetaAttribute(MetaAttribute) - Static method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder.PerParameterStatsDecoder.HistogramsDecoder.HistogramCountsDecoder
-
- binCountMinValue() - Static method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder.PerParameterStatsDecoder.HistogramsDecoder.HistogramCountsDecoder
-
- binCountMinValue() - Static method in class org.deeplearning4j.ui.stats.sbe.UpdateEncoder.PerParameterStatsEncoder.HistogramsEncoder.HistogramCountsEncoder
-
- binCountNullValue() - Static method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder.PerParameterStatsDecoder.HistogramsDecoder.HistogramCountsDecoder
-
- binCountNullValue() - Static method in class org.deeplearning4j.ui.stats.sbe.UpdateEncoder.PerParameterStatsEncoder.HistogramsEncoder.HistogramCountsEncoder
-
- binomial(RandomGenerator, int, double) - Static method in class org.deeplearning4j.clustering.util.MathUtils
-
Generates a binomial distributed number using
the given rng
- BinomialDistribution - Class in org.deeplearning4j.nn.conf.distribution
-
A binomial distribution.
- BinomialDistribution(int, double) - Constructor for class org.deeplearning4j.nn.conf.distribution.BinomialDistribution
-
Create a distribution
- BinomialSamplingPreProcessor - Class in org.deeplearning4j.nn.conf.preprocessor
-
Binomial sampling pre processor
- BinomialSamplingPreProcessor() - Constructor for class org.deeplearning4j.nn.conf.preprocessor.BinomialSamplingPreProcessor
-
- bitmapMode - Variable in class org.deeplearning4j.optimize.solvers.accumulation.EncodingHandler
-
- BlindInferenceCallable(VocabCache<VocabWord>, TokenizerFactory, String) - Constructor for class org.deeplearning4j.models.paragraphvectors.ParagraphVectors.BlindInferenceCallable
-
- BlindInferenceCallable(VocabCache<VocabWord>, TokenizerFactory, String, AtomicLong) - Constructor for class org.deeplearning4j.models.paragraphvectors.ParagraphVectors.BlindInferenceCallable
-
- BLOCK_LENGTH - Static variable in class org.deeplearning4j.ui.stats.sbe.StaticInfoDecoder
-
- BLOCK_LENGTH - Static variable in class org.deeplearning4j.ui.stats.sbe.StaticInfoEncoder
-
- BLOCK_LENGTH - Static variable in class org.deeplearning4j.ui.stats.sbe.StorageMetaDataDecoder
-
- BLOCK_LENGTH - Static variable in class org.deeplearning4j.ui.stats.sbe.StorageMetaDataEncoder
-
- BLOCK_LENGTH - Static variable in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder
-
- BLOCK_LENGTH - Static variable in class org.deeplearning4j.ui.stats.sbe.UpdateEncoder
-
- BlockingObserver - Class in org.deeplearning4j.spark.parameterserver.util
-
- BlockingObserver() - Constructor for class org.deeplearning4j.spark.parameterserver.util.BlockingObserver
-
- blockLength() - Method in class org.deeplearning4j.ui.stats.sbe.GroupSizeEncodingDecoder
-
- blockLength(int) - Method in class org.deeplearning4j.ui.stats.sbe.GroupSizeEncodingEncoder
-
- blockLength() - Method in class org.deeplearning4j.ui.stats.sbe.MessageHeaderDecoder
-
- blockLength(int) - Method in class org.deeplearning4j.ui.stats.sbe.MessageHeaderEncoder
-
- blockLengthMaxValue() - Static method in class org.deeplearning4j.ui.stats.sbe.GroupSizeEncodingDecoder
-
- blockLengthMaxValue() - Static method in class org.deeplearning4j.ui.stats.sbe.GroupSizeEncodingEncoder
-
- blockLengthMaxValue() - Static method in class org.deeplearning4j.ui.stats.sbe.MessageHeaderDecoder
-
- blockLengthMaxValue() - Static method in class org.deeplearning4j.ui.stats.sbe.MessageHeaderEncoder
-
- blockLengthMinValue() - Static method in class org.deeplearning4j.ui.stats.sbe.GroupSizeEncodingDecoder
-
- blockLengthMinValue() - Static method in class org.deeplearning4j.ui.stats.sbe.GroupSizeEncodingEncoder
-
- blockLengthMinValue() - Static method in class org.deeplearning4j.ui.stats.sbe.MessageHeaderDecoder
-
- blockLengthMinValue() - Static method in class org.deeplearning4j.ui.stats.sbe.MessageHeaderEncoder
-
- blockLengthNullValue() - Static method in class org.deeplearning4j.ui.stats.sbe.GroupSizeEncodingDecoder
-
- blockLengthNullValue() - Static method in class org.deeplearning4j.ui.stats.sbe.GroupSizeEncodingEncoder
-
- blockLengthNullValue() - Static method in class org.deeplearning4j.ui.stats.sbe.MessageHeaderDecoder
-
- blockLengthNullValue() - Static method in class org.deeplearning4j.ui.stats.sbe.MessageHeaderEncoder
-
- blocks - Variable in class org.deeplearning4j.nn.conf.layers.SpaceToBatchLayer
-
- blocks - Variable in class org.deeplearning4j.nn.conf.layers.SpaceToBatchLayer.Builder
-
- blocks(int[]) - Method in class org.deeplearning4j.nn.conf.layers.SpaceToBatchLayer.Builder
-
- blocks(int) - Method in class org.deeplearning4j.nn.conf.layers.SpaceToDepthLayer.Builder
-
- blockSize - Variable in class org.deeplearning4j.nn.conf.layers.SpaceToDepthLayer
-
- blockSize - Variable in class org.deeplearning4j.nn.conf.layers.SpaceToDepthLayer.Builder
-
- blockTillAllRunning() - Method in class org.deeplearning4j.aws.ec2.Ec2BoxCreator
-
- blockUntilDepleted() - Method in class org.deeplearning4j.spark.parameterserver.iterators.VirtualIterator
-
This method blocks until underlying Iterator is depleted
- blockUntilFinished() - Method in class org.deeplearning4j.spark.parameterserver.pw.SharedTrainingWrapper
-
- blowupBoxes() - Method in class org.deeplearning4j.aws.ec2.Ec2BoxCreator
-
- BookRecognition - Class in org.ansj.recognition.impl
-
基于规则的新词发现 jijiang feidiao
- BookRecognition() - Constructor for class org.ansj.recognition.impl.BookRecognition
-
- borderWidth(int) - Method in class org.deeplearning4j.ui.components.table.style.StyleTable.Builder
-
- boundary - Variable in class org.deeplearning4j.optimize.solvers.accumulation.EncodedGradientsAccumulator
-
- boundary - Variable in class org.deeplearning4j.optimize.solvers.accumulation.EncodedGradientsAccumulator.Builder
-
- boundary - Variable in class org.deeplearning4j.optimize.solvers.accumulation.EncodingHandler
-
- boundingBoxPriors(INDArray) - Method in class org.deeplearning4j.nn.conf.layers.objdetect.Yolo2OutputLayer.Builder
-
Bounding box priors dimensions [width, height].
- broadcastConfiguration - Variable in class org.deeplearning4j.spark.parameterserver.training.SharedTrainingMaster
-
- broadcastEnvironment(JavaSparkContext) - Method in class org.deeplearning4j.spark.models.sequencevectors.SparkSequenceVectors
-
- broadcastGradients(SharedGradient) - Method in class org.deeplearning4j.parallelism.ParallelWrapper
-
This method will propagate gradients across all workers
- broadcastModel - Variable in class org.deeplearning4j.spark.parameterserver.training.SharedTrainingMaster
-
- broadcastUpdates(INDArray) - Method in class org.deeplearning4j.optimize.solvers.accumulation.EncodingHandler
-
- broadcastUpdates(INDArray) - Method in class org.deeplearning4j.optimize.solvers.accumulation.LocalHandler
-
- broadcastUpdates(INDArray) - Method in interface org.deeplearning4j.optimize.solvers.accumulation.MessageHandler
-
This method does broadcast of given update message across network
- bucket(INDArray) - Method in interface org.deeplearning4j.clustering.lsh.LSH
-
Returns the set of all vectors that could approximately be considered negihbors of the query,
without selection on the basis of distance or number of neighbors.
- bucket(INDArray) - Method in class org.deeplearning4j.clustering.lsh.RandomProjectionLSH
-
- BucketIterator - Class in org.deeplearning4j.aws.s3.reader
-
Iterator over individual S3 bucket
- BucketIterator(String) - Constructor for class org.deeplearning4j.aws.s3.reader.BucketIterator
-
- BucketIterator(String, S3Downloader) - Constructor for class org.deeplearning4j.aws.s3.reader.BucketIterator
-
- BucketKeyListener - Interface in org.deeplearning4j.aws.s3.reader
-
When paginating through a result applyTransformToDestination,
allows the user to react to a bucket result being found
- buckets() - Method in class org.deeplearning4j.aws.s3.reader.S3Downloader
-
Returns the list of buckets in s3
- buffer - Variable in class org.deeplearning4j.datasets.iterator.AsyncDataSetIterator
-
- buffer - Variable in class org.deeplearning4j.datasets.iterator.AsyncMultiDataSetIterator
-
- buffer - Variable in class org.deeplearning4j.models.sequencevectors.transformers.impl.iterables.ParallelTransformerIterator
-
- buffer - Variable in class org.deeplearning4j.parallelism.AsyncIterator
-
- BUFFER_SIZE - Static variable in class org.deeplearning4j.spark.data.PathToDataSetFunction
-
- BUFFER_SIZE - Static variable in class org.deeplearning4j.spark.data.PathToMultiDataSetFunction
-
- BUFFER_SIZE - Static variable in class org.deeplearning4j.spark.iterator.PathSparkDataSetIterator
-
- BUFFER_SIZE - Static variable in class org.deeplearning4j.spark.iterator.PathSparkMultiDataSetIterator
-
- BUFFER_SIZE - Static variable in class org.deeplearning4j.spark.util.data.validation.ValidateDataSetFn
-
- BUFFER_SIZE - Static variable in class org.deeplearning4j.spark.util.data.validation.ValidateMultiDataSetFn
-
- bufferEntries - Variable in class com.atilika.kuromoji.compile.TokenInfoDictionaryCompilerBase
-
- BufferEntry - Class in com.atilika.kuromoji.buffer
-
- BufferEntry() - Constructor for class com.atilika.kuromoji.buffer.BufferEntry
-
- bufferSize - Variable in class org.deeplearning4j.spark.parameterserver.conf.SharedTrainingConfiguration
-
This value **overrides** bufferSize calculations for gradients accumulator
- bufferSize - Variable in class org.deeplearning4j.text.documentiterator.AsyncLabelAwareIterator
-
- bufferSizePerDevice - Variable in class org.deeplearning4j.datasets.iterator.parallel.JointParallelDataSetIterator
-
- build(String, String, String, boolean) - Method in class com.atilika.kuromoji.compile.DictionaryCompilerBase
-
- build(String[]) - Method in class com.atilika.kuromoji.compile.DictionaryCompilerBase
-
- build(List<String>, boolean) - Static method in class com.atilika.kuromoji.compile.DoubleArrayTrieCompiler
-
- build() - Method in class com.atilika.kuromoji.dict.GenericDictionaryEntry.Builder
-
- build() - Method in class com.atilika.kuromoji.ipadic.Tokenizer.Builder
-
Creates the custom tokenizer instance
- build() - Method in class com.atilika.kuromoji.TokenizerBase.Builder
-
Creates a Tokenizer instance defined by this Builder
- build(Trie) - Method in class com.atilika.kuromoji.trie.DoubleArrayTrie
-
Construct double array trie which is equivalent to input trie
- build(String) - Method in class com.atilika.kuromoji.viterbi.ViterbiBuilder
-
Build lattice from input text
- build() - Method in class org.deeplearning4j.aws.emr.SparkEMRClient.Builder
-
Creates an EMR Spark cluster deployment
- build() - Method in class org.deeplearning4j.bagofwords.vectorizer.BagOfWordsVectorizer.Builder
-
- build() - Method in class org.deeplearning4j.bagofwords.vectorizer.Builder
-
Deprecated.
- build() - Method in class org.deeplearning4j.bagofwords.vectorizer.TfidfVectorizer.Builder
-
- build() - Method in class org.deeplearning4j.datasets.datavec.RecordReaderDataSetIterator.Builder
-
- build() - Method in class org.deeplearning4j.datasets.datavec.RecordReaderMultiDataSetIterator.Builder
-
Create the RecordReaderMultiDataSetIterator
- build() - Method in class org.deeplearning4j.datasets.iterator.CombinedMultiDataSetPreProcessor.Builder
-
- build() - Method in class org.deeplearning4j.datasets.iterator.CombinedPreProcessor.Builder
-
- build() - Method in class org.deeplearning4j.datasets.iterator.parallel.JointParallelDataSetIterator.Builder
-
- build() - Method in class org.deeplearning4j.earlystopping.EarlyStoppingConfiguration.Builder
-
Create the early stopping configuration
- build() - Method in class org.deeplearning4j.graph.models.deepwalk.DeepWalk.Builder
-
- build() - Method in class org.deeplearning4j.iterator.CnnSentenceDataSetIterator.Builder
-
- build() - Method in class org.deeplearning4j.models.embeddings.inmemory.InMemoryLookupTable.Builder
-
- build() - Method in class org.deeplearning4j.models.embeddings.learning.impl.elements.GloVe.Builder
-
- build() - Method in class org.deeplearning4j.models.glove.AbstractCoOccurrences.Builder
-
- build() - Method in class org.deeplearning4j.models.glove.Glove.Builder
-
- build() - Method in class org.deeplearning4j.models.glove.GloveWeightLookupTable.Builder
-
Deprecated.
- build() - Method in class org.deeplearning4j.models.node2vec.Node2Vec.Builder
-
Deprecated.
- build() - Method in class org.deeplearning4j.models.paragraphvectors.ParagraphVectors.Builder
-
- build() - Method in class org.deeplearning4j.models.sequencevectors.graph.walkers.impl.NearestVertexWalker.Builder
-
This method returns you new GraphWalker instance
- build() - Method in class org.deeplearning4j.models.sequencevectors.graph.walkers.impl.PopularityWalker.Builder
-
This method builds PopularityWalker object with previously specified params
- build() - Method in class org.deeplearning4j.models.sequencevectors.graph.walkers.impl.RandomWalker.Builder
-
This method builds RandomWalker instance
- build() - Method in class org.deeplearning4j.models.sequencevectors.graph.walkers.impl.WeightedWalker.Builder
-
- build() - Method in class org.deeplearning4j.models.sequencevectors.iterators.AbstractSequenceIterator.Builder
-
Builds SequenceIterator
- build() - Method in class org.deeplearning4j.models.sequencevectors.listeners.SerializingListener.Builder
-
This method returns new SerializingListener instance
- build() - Method in class org.deeplearning4j.models.sequencevectors.SequenceVectors.Builder
-
Build SequenceVectors instance with defined settings/options
- build() - Method in class org.deeplearning4j.models.sequencevectors.transformers.impl.GraphTransformer.Builder
-
- build() - Method in class org.deeplearning4j.models.sequencevectors.transformers.impl.SentenceTransformer.Builder
-
- build() - Method in class org.deeplearning4j.models.word2vec.Huffman
-
- build() - Method in class org.deeplearning4j.models.word2vec.StaticWord2Vec.Builder
-
This method returns Static Word2Vec implementation, which is suitable for tasks like neural nets feeding.
- build() - Method in class org.deeplearning4j.models.word2vec.Word2Vec.Builder
-
- build() - Method in class org.deeplearning4j.models.word2vec.wordstore.inmemory.AbstractCache.Builder
-
- build() - Method in class org.deeplearning4j.models.word2vec.wordstore.VocabConstructor.Builder
-
- build() - Method in class org.deeplearning4j.models.word2vec.wordstore.VocabularyHolder.Builder
-
- build() - Method in class org.deeplearning4j.nn.conf.ComputationGraphConfiguration.GraphBuilder
-
Create the ComputationGraphConfiguration from the Builder pattern
- build() - Method in class org.deeplearning4j.nn.conf.layers.ActivationLayer.Builder
-
- build() - Method in class org.deeplearning4j.nn.conf.layers.AutoEncoder.Builder
-
- build() - Method in class org.deeplearning4j.nn.conf.layers.BatchNormalization.Builder
-
- build() - Method in class org.deeplearning4j.nn.conf.layers.CenterLossOutputLayer.Builder
-
- build() - Method in class org.deeplearning4j.nn.conf.layers.CnnLossLayer.Builder
-
- build() - Method in class org.deeplearning4j.nn.conf.layers.Convolution1DLayer.Builder
-
- build() - Method in class org.deeplearning4j.nn.conf.layers.Convolution3D.Builder
-
- build() - Method in class org.deeplearning4j.nn.conf.layers.convolutional.Cropping1D.Builder
-
- build() - Method in class org.deeplearning4j.nn.conf.layers.convolutional.Cropping2D.Builder
-
- build() - Method in class org.deeplearning4j.nn.conf.layers.convolutional.Cropping3D.Builder
-
- build() - Method in class org.deeplearning4j.nn.conf.layers.ConvolutionLayer.Builder
-
- build() - Method in class org.deeplearning4j.nn.conf.layers.Deconvolution2D.Builder
-
- build() - Method in class org.deeplearning4j.nn.conf.layers.DenseLayer.Builder
-
- build() - Method in class org.deeplearning4j.nn.conf.layers.DepthwiseConvolution2D.Builder
-
- build() - Method in class org.deeplearning4j.nn.conf.layers.DropoutLayer.Builder
-
- build() - Method in class org.deeplearning4j.nn.conf.layers.EmbeddingLayer.Builder
-
- build() - Method in class org.deeplearning4j.nn.conf.layers.EmbeddingSequenceLayer.Builder
-
- build() - Method in class org.deeplearning4j.nn.conf.layers.GlobalPoolingLayer.Builder
-
- build() - Method in class org.deeplearning4j.nn.conf.layers.GravesBidirectionalLSTM.Builder
-
Deprecated.
- build() - Method in class org.deeplearning4j.nn.conf.layers.GravesLSTM.Builder
-
- build() - Method in class org.deeplearning4j.nn.conf.layers.Layer.Builder
-
- build() - Method in class org.deeplearning4j.nn.conf.layers.LocalResponseNormalization.Builder
-
- build() - Method in class org.deeplearning4j.nn.conf.layers.LossLayer.Builder
-
- build() - Method in class org.deeplearning4j.nn.conf.layers.LSTM.Builder
-
- build() - Method in class org.deeplearning4j.nn.conf.layers.misc.ElementWiseMultiplicationLayer.Builder
-
- build() - Method in class org.deeplearning4j.nn.conf.layers.misc.FrozenLayer.Builder
-
- build() - Method in class org.deeplearning4j.nn.conf.layers.objdetect.Yolo2OutputLayer.Builder
-
- build() - Method in class org.deeplearning4j.nn.conf.layers.OutputLayer.Builder
-
- build() - Method in class org.deeplearning4j.nn.conf.layers.recurrent.Bidirectional.Builder
-
- build() - Method in class org.deeplearning4j.nn.conf.layers.recurrent.SimpleRnn.Builder
-
- build() - Method in class org.deeplearning4j.nn.conf.layers.RnnLossLayer.Builder
-
- build() - Method in class org.deeplearning4j.nn.conf.layers.RnnOutputLayer.Builder
-
- build() - Method in class org.deeplearning4j.nn.conf.layers.SeparableConvolution2D.Builder
-
- build() - Method in class org.deeplearning4j.nn.conf.layers.SpaceToBatchLayer.Builder
-
- build() - Method in class org.deeplearning4j.nn.conf.layers.SpaceToDepthLayer.Builder
-
- build() - Method in class org.deeplearning4j.nn.conf.layers.Subsampling1DLayer.Builder
-
- build() - Method in class org.deeplearning4j.nn.conf.layers.Subsampling3DLayer.Builder
-
- build() - Method in class org.deeplearning4j.nn.conf.layers.SubsamplingLayer.Builder
-
- build() - Method in class org.deeplearning4j.nn.conf.layers.Upsampling1D.Builder
-
- build() - Method in class org.deeplearning4j.nn.conf.layers.Upsampling2D.Builder
-
- build() - Method in class org.deeplearning4j.nn.conf.layers.Upsampling3D.Builder
-
- build() - Method in class org.deeplearning4j.nn.conf.layers.variational.CompositeReconstructionDistribution.Builder
-
- build() - Method in class org.deeplearning4j.nn.conf.layers.variational.VariationalAutoencoder.Builder
-
- build() - Method in class org.deeplearning4j.nn.conf.layers.ZeroPadding1DLayer.Builder
-
- build() - Method in class org.deeplearning4j.nn.conf.layers.ZeroPadding3DLayer.Builder
-
- build() - Method in class org.deeplearning4j.nn.conf.layers.ZeroPaddingLayer.Builder
-
- build() - Method in class org.deeplearning4j.nn.conf.memory.LayerMemoryReport.Builder
-
- build() - Method in class org.deeplearning4j.nn.conf.MultiLayerConfiguration.Builder
-
- build() - Method in class org.deeplearning4j.nn.conf.NeuralNetConfiguration.Builder
-
Return a configuration based on this builder
- build() - Method in class org.deeplearning4j.nn.conf.NeuralNetConfiguration.ListBuilder
-
Build the multi layer network
based on this neural network and
overr ridden parameters
- build() - Method in class org.deeplearning4j.nn.conf.ocnn.OCNNOutputLayer.Builder
-
- build() - Method in class org.deeplearning4j.nn.transferlearning.FineTuneConfiguration.Builder
-
- build() - Method in class org.deeplearning4j.nn.transferlearning.TransferLearning.Builder
-
Returns a model with the fine tune configuration and specified architecture changes.
- build() - Method in class org.deeplearning4j.nn.transferlearning.TransferLearning.GraphBuilder
-
Returns a computation graph build to specifications.
- build() - Method in class org.deeplearning4j.nn.workspace.LayerWorkspaceMgr.Builder
-
- build() - Method in class org.deeplearning4j.optimize.listeners.checkpoint.CheckpointListener.Builder
-
- build() - Method in class org.deeplearning4j.optimize.listeners.PerformanceListener.Builder
-
This method returns configured PerformanceListener instance
- build() - Method in class org.deeplearning4j.optimize.Solver.Builder
-
- build() - Method in class org.deeplearning4j.optimize.solvers.accumulation.EncodedGradientsAccumulator.Builder
-
- build() - Method in class org.deeplearning4j.parallelism.MagicQueue.Builder
-
Deprecated.
- build() - Method in class org.deeplearning4j.parallelism.ParallelInference.Builder
-
This method builds new ParallelInference instance
- build() - Method in class org.deeplearning4j.parallelism.ParallelWrapper.Builder
-
This method returns ParallelWrapper instance
- build() - Method in class org.deeplearning4j.perf.listener.SystemPolling.Builder
-
- build() - Method in class org.deeplearning4j.plot.BarnesHutTsne.Builder
-
- build() - Method in class org.deeplearning4j.plot.Tsne.Builder
-
- build() - Method in class org.deeplearning4j.spark.api.stats.CommonSparkTrainingStats.Builder
-
- build(SparkTrainingStats) - Method in class org.deeplearning4j.spark.api.stats.StatsCalculationHelper
-
- build() - Method in class org.deeplearning4j.spark.impl.paramavg.ParameterAveragingTrainingMaster.Builder
-
- build() - Method in class org.deeplearning4j.spark.impl.paramavg.stats.ParameterAveragingTrainingMasterStats.ParameterAveragingTrainingMasterStatsHelper
-
- build() - Method in class org.deeplearning4j.spark.impl.paramavg.stats.ParameterAveragingTrainingWorkerStats.ParameterAveragingTrainingWorkerStatsHelper
-
- build() - Method in class org.deeplearning4j.spark.models.embeddings.glove.GloveParam.Builder
-
- build() - Method in class org.deeplearning4j.spark.models.embeddings.word2vec.Word2Vec.Builder
-
- build() - Method in class org.deeplearning4j.spark.models.embeddings.word2vec.Word2VecParam.Builder
-
Deprecated.
- build() - Method in class org.deeplearning4j.spark.models.sequencevectors.SparkSequenceVectors.Builder
-
- build() - Method in class org.deeplearning4j.spark.models.word2vec.SparkWord2Vec.Builder
-
This method returns you SparkWord2Vec instance ready for training
- build() - Method in class org.deeplearning4j.spark.parameterserver.training.SharedTrainingMaster.Builder
-
- build() - Method in class org.deeplearning4j.streaming.routes.CamelKafkaRouteBuilder.Builder
-
- build() - Method in class org.deeplearning4j.text.documentiterator.BasicLabelAwareIterator.Builder
-
- build() - Method in class org.deeplearning4j.text.documentiterator.FileLabelAwareIterator.Builder
-
- build() - Method in class org.deeplearning4j.text.documentiterator.FilenamesLabelAwareIterator.Builder
-
- build() - Method in class org.deeplearning4j.text.sentenceiterator.AggregatingSentenceIterator.Builder
-
- build() - Method in class org.deeplearning4j.text.sentenceiterator.PrefetchingSentenceIterator.Builder
-
Deprecated.
- build() - Method in class org.deeplearning4j.text.sentenceiterator.StreamLineIterator.Builder
-
- build() - Method in class org.deeplearning4j.ui.components.chart.ChartHistogram.Builder
-
- build() - Method in class org.deeplearning4j.ui.components.chart.ChartHorizontalBar.Builder
-
- build() - Method in class org.deeplearning4j.ui.components.chart.ChartLine.Builder
-
- build() - Method in class org.deeplearning4j.ui.components.chart.ChartScatter.Builder
-
- build() - Method in class org.deeplearning4j.ui.components.chart.ChartStackedArea.Builder
-
- build() - Method in class org.deeplearning4j.ui.components.chart.ChartTimeline.Builder
-
- build() - Method in class org.deeplearning4j.ui.components.chart.style.StyleChart.Builder
-
- build() - Method in class org.deeplearning4j.ui.components.component.style.StyleDiv.Builder
-
- build() - Method in class org.deeplearning4j.ui.components.decorator.DecoratorAccordion.Builder
-
- build() - Method in class org.deeplearning4j.ui.components.decorator.style.StyleAccordion.Builder
-
- build() - Method in class org.deeplearning4j.ui.components.table.ComponentTable.Builder
-
- build() - Method in class org.deeplearning4j.ui.components.table.style.StyleTable.Builder
-
- build() - Method in class org.deeplearning4j.ui.components.text.ComponentText.Builder
-
- build() - Method in class org.deeplearning4j.ui.components.text.style.StyleText.Builder
-
- build() - Method in class org.deeplearning4j.ui.stats.impl.DefaultStatsUpdateConfiguration.Builder
-
- build() - Method in class org.deeplearning4j.ui.storage.mapdb.MapDBStatsStorage.Builder
-
- build() - Method in class org.deeplearning4j.ui.UiConnectionInfo.Builder
-
- build() - Method in class org.deeplearning4j.ui.weights.HistogramBin.Builder
-
Returns ready-to-use Histogram instance
- buildCumSum() - Method in class org.deeplearning4j.spark.text.functions.CountCumSum
-
- Builder() - Constructor for class com.atilika.kuromoji.dict.GenericDictionaryEntry.Builder
-
- Builder() - Constructor for class com.atilika.kuromoji.ipadic.Tokenizer.Builder
-
Creates a default builder
- Builder() - Constructor for class com.atilika.kuromoji.TokenizerBase.Builder
-
- Builder() - Constructor for class org.deeplearning4j.aws.emr.SparkEMRClient.Builder
-
- Builder() - Constructor for class org.deeplearning4j.bagofwords.vectorizer.BagOfWordsVectorizer.Builder
-
- Builder - Class in org.deeplearning4j.bagofwords.vectorizer
-
Deprecated.
- Builder() - Constructor for class org.deeplearning4j.bagofwords.vectorizer.Builder
-
Deprecated.
- Builder() - Constructor for class org.deeplearning4j.bagofwords.vectorizer.TfidfVectorizer.Builder
-
- Builder() - Constructor for class org.deeplearning4j.BasePipeline.Builder
-
- Builder(RecordReader, int) - Constructor for class org.deeplearning4j.datasets.datavec.RecordReaderDataSetIterator.Builder
-
- Builder(int) - Constructor for class org.deeplearning4j.datasets.datavec.RecordReaderMultiDataSetIterator.Builder
-
- Builder() - Constructor for class org.deeplearning4j.datasets.iterator.CombinedMultiDataSetPreProcessor.Builder
-
- Builder() - Constructor for class org.deeplearning4j.datasets.iterator.CombinedPreProcessor.Builder
-
- Builder(InequalityHandling) - Constructor for class org.deeplearning4j.datasets.iterator.parallel.JointParallelDataSetIterator.Builder
-
- Builder(List<DataSetIterator>, InequalityHandling) - Constructor for class org.deeplearning4j.datasets.iterator.parallel.JointParallelDataSetIterator.Builder
-
- Builder() - Constructor for class org.deeplearning4j.earlystopping.EarlyStoppingConfiguration.Builder
-
- Builder() - Constructor for class org.deeplearning4j.graph.models.deepwalk.DeepWalk.Builder
-
- Builder() - Constructor for class org.deeplearning4j.iterator.CnnSentenceDataSetIterator.Builder
-
- Builder() - Constructor for class org.deeplearning4j.models.embeddings.inmemory.InMemoryLookupTable.Builder
-
- Builder() - Constructor for class org.deeplearning4j.models.embeddings.learning.impl.elements.GloVe.Builder
-
- Builder() - Constructor for class org.deeplearning4j.models.glove.AbstractCoOccurrences.Builder
-
- Builder() - Constructor for class org.deeplearning4j.models.glove.Glove.Builder
-
- Builder(VectorsConfiguration) - Constructor for class org.deeplearning4j.models.glove.Glove.Builder
-
- Builder() - Constructor for class org.deeplearning4j.models.glove.GloveWeightLookupTable.Builder
-
Deprecated.
- Builder(GraphWalker<V>, VectorsConfiguration) - Constructor for class org.deeplearning4j.models.node2vec.Node2Vec.Builder
-
Deprecated.
- Builder() - Constructor for class org.deeplearning4j.models.paragraphvectors.ParagraphVectors.Builder
-
- Builder(VectorsConfiguration) - Constructor for class org.deeplearning4j.models.paragraphvectors.ParagraphVectors.Builder
-
- Builder(IGraph<V, ?>) - Constructor for class org.deeplearning4j.models.sequencevectors.graph.walkers.impl.NearestVertexWalker.Builder
-
- Builder(IGraph<T, ?>) - Constructor for class org.deeplearning4j.models.sequencevectors.graph.walkers.impl.PopularityWalker.Builder
-
- Builder(IGraph<T, ?>) - Constructor for class org.deeplearning4j.models.sequencevectors.graph.walkers.impl.RandomWalker.Builder
-
Builder constructor for RandomWalker
- Builder(IGraph<T, ? extends Number>) - Constructor for class org.deeplearning4j.models.sequencevectors.graph.walkers.impl.WeightedWalker.Builder
-
- Builder(Iterable<Sequence<T>>) - Constructor for class org.deeplearning4j.models.sequencevectors.iterators.AbstractSequenceIterator.Builder
-
Builds AbstractSequenceIterator on top of Iterable object
- Builder(ListenerEvent, int) - Constructor for class org.deeplearning4j.models.sequencevectors.listeners.SerializingListener.Builder
-
- Builder() - Constructor for class org.deeplearning4j.models.sequencevectors.SequenceVectors.Builder
-
- Builder(VectorsConfiguration) - Constructor for class org.deeplearning4j.models.sequencevectors.SequenceVectors.Builder
-
- Builder() - Constructor for class org.deeplearning4j.models.sequencevectors.transformers.impl.GraphTransformer.Builder
-
- Builder(GraphWalker<T>) - Constructor for class org.deeplearning4j.models.sequencevectors.transformers.impl.GraphTransformer.Builder
-
- Builder(IGraph<T, ?>) - Constructor for class org.deeplearning4j.models.sequencevectors.transformers.impl.GraphTransformer.Builder
-
- Builder() - Constructor for class org.deeplearning4j.models.sequencevectors.transformers.impl.SentenceTransformer.Builder
-
- Builder(AbstractStorage<Integer>, VocabCache<VocabWord>) - Constructor for class org.deeplearning4j.models.word2vec.StaticWord2Vec.Builder
-
- Builder() - Constructor for class org.deeplearning4j.models.word2vec.Word2Vec.Builder
-
- Builder(VectorsConfiguration) - Constructor for class org.deeplearning4j.models.word2vec.Word2Vec.Builder
-
- Builder() - Constructor for class org.deeplearning4j.models.word2vec.wordstore.inmemory.AbstractCache.Builder
-
- Builder() - Constructor for class org.deeplearning4j.models.word2vec.wordstore.VocabConstructor.Builder
-
- Builder() - Constructor for class org.deeplearning4j.models.word2vec.wordstore.VocabularyHolder.Builder
-
- Builder() - Constructor for class org.deeplearning4j.nn.conf.layers.AbstractLSTM.Builder
-
- Builder() - Constructor for class org.deeplearning4j.nn.conf.layers.ActivationLayer.Builder
-
- Builder() - Constructor for class org.deeplearning4j.nn.conf.layers.AutoEncoder.Builder
-
- Builder(double) - Constructor for class org.deeplearning4j.nn.conf.layers.AutoEncoder.Builder
-
- Builder() - Constructor for class org.deeplearning4j.nn.conf.layers.BaseLayer.Builder
-
- Builder() - Constructor for class org.deeplearning4j.nn.conf.layers.BaseOutputLayer.Builder
-
- Builder(LossFunctions.LossFunction) - Constructor for class org.deeplearning4j.nn.conf.layers.BaseOutputLayer.Builder
-
- Builder(ILossFunction) - Constructor for class org.deeplearning4j.nn.conf.layers.BaseOutputLayer.Builder
-
- Builder() - Constructor for class org.deeplearning4j.nn.conf.layers.BasePretrainNetwork.Builder
-
- Builder() - Constructor for class org.deeplearning4j.nn.conf.layers.BaseRecurrentLayer.Builder
-
- Builder(double, boolean) - Constructor for class org.deeplearning4j.nn.conf.layers.BatchNormalization.Builder
-
- Builder(double, double) - Constructor for class org.deeplearning4j.nn.conf.layers.BatchNormalization.Builder
-
- Builder(double, double, boolean) - Constructor for class org.deeplearning4j.nn.conf.layers.BatchNormalization.Builder
-
- Builder(boolean) - Constructor for class org.deeplearning4j.nn.conf.layers.BatchNormalization.Builder
-
- Builder() - Constructor for class org.deeplearning4j.nn.conf.layers.BatchNormalization.Builder
-
- Builder(LossFunctions.LossFunction) - Constructor for class org.deeplearning4j.nn.conf.layers.CenterLossOutputLayer.Builder
-
- Builder(ILossFunction) - Constructor for class org.deeplearning4j.nn.conf.layers.CenterLossOutputLayer.Builder
-
- Builder() - Constructor for class org.deeplearning4j.nn.conf.layers.CnnLossLayer.Builder
-
- Builder(LossFunctions.LossFunction) - Constructor for class org.deeplearning4j.nn.conf.layers.CnnLossLayer.Builder
-
- Builder(ILossFunction) - Constructor for class org.deeplearning4j.nn.conf.layers.CnnLossLayer.Builder
-
- Builder() - Constructor for class org.deeplearning4j.nn.conf.layers.Convolution1DLayer.Builder
-
- Builder(int, int) - Constructor for class org.deeplearning4j.nn.conf.layers.Convolution1DLayer.Builder
-
- Builder(int) - Constructor for class org.deeplearning4j.nn.conf.layers.Convolution1DLayer.Builder
-
- Builder(int, int, int) - Constructor for class org.deeplearning4j.nn.conf.layers.Convolution1DLayer.Builder
-
- Builder() - Constructor for class org.deeplearning4j.nn.conf.layers.Convolution3D.Builder
-
- Builder(int[], int[], int[]) - Constructor for class org.deeplearning4j.nn.conf.layers.Convolution3D.Builder
-
- Builder(int[], int[]) - Constructor for class org.deeplearning4j.nn.conf.layers.Convolution3D.Builder
-
- Builder(int...) - Constructor for class org.deeplearning4j.nn.conf.layers.Convolution3D.Builder
-
- Builder() - Constructor for class org.deeplearning4j.nn.conf.layers.convolutional.Cropping1D.Builder
-
- Builder(int[]) - Constructor for class org.deeplearning4j.nn.conf.layers.convolutional.Cropping1D.Builder
-
- Builder(int) - Constructor for class org.deeplearning4j.nn.conf.layers.convolutional.Cropping1D.Builder
-
- Builder(int, int) - Constructor for class org.deeplearning4j.nn.conf.layers.convolutional.Cropping1D.Builder
-
- Builder() - Constructor for class org.deeplearning4j.nn.conf.layers.convolutional.Cropping2D.Builder
-
- Builder(int[]) - Constructor for class org.deeplearning4j.nn.conf.layers.convolutional.Cropping2D.Builder
-
- Builder(int, int) - Constructor for class org.deeplearning4j.nn.conf.layers.convolutional.Cropping2D.Builder
-
- Builder(int, int, int, int) - Constructor for class org.deeplearning4j.nn.conf.layers.convolutional.Cropping2D.Builder
-
- Builder() - Constructor for class org.deeplearning4j.nn.conf.layers.convolutional.Cropping3D.Builder
-
- Builder(int[]) - Constructor for class org.deeplearning4j.nn.conf.layers.convolutional.Cropping3D.Builder
-
- Builder(int, int, int) - Constructor for class org.deeplearning4j.nn.conf.layers.convolutional.Cropping3D.Builder
-
- Builder(int, int, int, int, int, int) - Constructor for class org.deeplearning4j.nn.conf.layers.convolutional.Cropping3D.Builder
-
- Builder(int[], int[], int[]) - Constructor for class org.deeplearning4j.nn.conf.layers.ConvolutionLayer.Builder
-
- Builder(int[], int[]) - Constructor for class org.deeplearning4j.nn.conf.layers.ConvolutionLayer.Builder
-
- Builder(int...) - Constructor for class org.deeplearning4j.nn.conf.layers.ConvolutionLayer.Builder
-
- Builder() - Constructor for class org.deeplearning4j.nn.conf.layers.ConvolutionLayer.Builder
-
- Builder(int[], int[], int[]) - Constructor for class org.deeplearning4j.nn.conf.layers.Deconvolution2D.Builder
-
- Builder(int[], int[]) - Constructor for class org.deeplearning4j.nn.conf.layers.Deconvolution2D.Builder
-
- Builder(int...) - Constructor for class org.deeplearning4j.nn.conf.layers.Deconvolution2D.Builder
-
- Builder() - Constructor for class org.deeplearning4j.nn.conf.layers.Deconvolution2D.Builder
-
- Builder() - Constructor for class org.deeplearning4j.nn.conf.layers.DenseLayer.Builder
-
- Builder(int[], int[], int[]) - Constructor for class org.deeplearning4j.nn.conf.layers.DepthwiseConvolution2D.Builder
-
- Builder(int[], int[]) - Constructor for class org.deeplearning4j.nn.conf.layers.DepthwiseConvolution2D.Builder
-
- Builder(int...) - Constructor for class org.deeplearning4j.nn.conf.layers.DepthwiseConvolution2D.Builder
-
- Builder() - Constructor for class org.deeplearning4j.nn.conf.layers.DepthwiseConvolution2D.Builder
-
- Builder(double) - Constructor for class org.deeplearning4j.nn.conf.layers.DropoutLayer.Builder
-
- Builder(IDropout) - Constructor for class org.deeplearning4j.nn.conf.layers.DropoutLayer.Builder
-
- Builder() - Constructor for class org.deeplearning4j.nn.conf.layers.EmbeddingLayer.Builder
-
- Builder() - Constructor for class org.deeplearning4j.nn.conf.layers.EmbeddingSequenceLayer.Builder
-
- Builder() - Constructor for class org.deeplearning4j.nn.conf.layers.FeedForwardLayer.Builder
-
- Builder() - Constructor for class org.deeplearning4j.nn.conf.layers.GlobalPoolingLayer.Builder
-
- Builder(PoolingType) - Constructor for class org.deeplearning4j.nn.conf.layers.GlobalPoolingLayer.Builder
-
- Builder() - Constructor for class org.deeplearning4j.nn.conf.layers.GravesBidirectionalLSTM.Builder
-
Deprecated.
- Builder() - Constructor for class org.deeplearning4j.nn.conf.layers.GravesLSTM.Builder
-
- Builder() - Constructor for class org.deeplearning4j.nn.conf.layers.Layer.Builder
-
- Builder(double, double, double) - Constructor for class org.deeplearning4j.nn.conf.layers.LocalResponseNormalization.Builder
-
- Builder() - Constructor for class org.deeplearning4j.nn.conf.layers.LocalResponseNormalization.Builder
-
- Builder() - Constructor for class org.deeplearning4j.nn.conf.layers.LossLayer.Builder
-
- Builder(LossFunctions.LossFunction) - Constructor for class org.deeplearning4j.nn.conf.layers.LossLayer.Builder
-
- Builder(ILossFunction) - Constructor for class org.deeplearning4j.nn.conf.layers.LossLayer.Builder
-
- Builder() - Constructor for class org.deeplearning4j.nn.conf.layers.LSTM.Builder
-
- Builder() - Constructor for class org.deeplearning4j.nn.conf.layers.misc.ElementWiseMultiplicationLayer.Builder
-
- Builder() - Constructor for class org.deeplearning4j.nn.conf.layers.misc.FrozenLayer.Builder
-
- Builder() - Constructor for class org.deeplearning4j.nn.conf.layers.objdetect.Yolo2OutputLayer.Builder
-
- Builder(LossFunctions.LossFunction) - Constructor for class org.deeplearning4j.nn.conf.layers.OutputLayer.Builder
-
- Builder(ILossFunction) - Constructor for class org.deeplearning4j.nn.conf.layers.OutputLayer.Builder
-
- Builder() - Constructor for class org.deeplearning4j.nn.conf.layers.recurrent.Bidirectional.Builder
-
- Builder() - Constructor for class org.deeplearning4j.nn.conf.layers.recurrent.SimpleRnn.Builder
-
- Builder() - Constructor for class org.deeplearning4j.nn.conf.layers.RnnLossLayer.Builder
-
- Builder(LossFunctions.LossFunction) - Constructor for class org.deeplearning4j.nn.conf.layers.RnnLossLayer.Builder
-
- Builder(ILossFunction) - Constructor for class org.deeplearning4j.nn.conf.layers.RnnLossLayer.Builder
-
- Builder() - Constructor for class org.deeplearning4j.nn.conf.layers.RnnOutputLayer.Builder
-
- Builder(LossFunctions.LossFunction) - Constructor for class org.deeplearning4j.nn.conf.layers.RnnOutputLayer.Builder
-
- Builder(ILossFunction) - Constructor for class org.deeplearning4j.nn.conf.layers.RnnOutputLayer.Builder
-
- Builder() - Constructor for class org.deeplearning4j.nn.conf.layers.samediff.AbstractSameDiffLayer.Builder
-
- Builder() - Constructor for class org.deeplearning4j.nn.conf.layers.samediff.BaseSameDiffLayer.Builder
-
- Builder(int[], int[], int[]) - Constructor for class org.deeplearning4j.nn.conf.layers.SeparableConvolution2D.Builder
-
- Builder(int[], int[]) - Constructor for class org.deeplearning4j.nn.conf.layers.SeparableConvolution2D.Builder
-
- Builder(int...) - Constructor for class org.deeplearning4j.nn.conf.layers.SeparableConvolution2D.Builder
-
- Builder() - Constructor for class org.deeplearning4j.nn.conf.layers.SeparableConvolution2D.Builder
-
- Builder(int[]) - Constructor for class org.deeplearning4j.nn.conf.layers.SpaceToBatchLayer.Builder
-
- Builder(int[], int[][]) - Constructor for class org.deeplearning4j.nn.conf.layers.SpaceToBatchLayer.Builder
-
- Builder(int) - Constructor for class org.deeplearning4j.nn.conf.layers.SpaceToDepthLayer.Builder
-
- Builder(int, SpaceToDepthLayer.DataFormat) - Constructor for class org.deeplearning4j.nn.conf.layers.SpaceToDepthLayer.Builder
-
- Builder(SubsamplingLayer.PoolingType, int, int) - Constructor for class org.deeplearning4j.nn.conf.layers.Subsampling1DLayer.Builder
-
- Builder(SubsamplingLayer.PoolingType, int) - Constructor for class org.deeplearning4j.nn.conf.layers.Subsampling1DLayer.Builder
-
- Builder(PoolingType, int) - Constructor for class org.deeplearning4j.nn.conf.layers.Subsampling1DLayer.Builder
-
- Builder(int, int, int) - Constructor for class org.deeplearning4j.nn.conf.layers.Subsampling1DLayer.Builder
-
- Builder(int, int) - Constructor for class org.deeplearning4j.nn.conf.layers.Subsampling1DLayer.Builder
-
- Builder(int) - Constructor for class org.deeplearning4j.nn.conf.layers.Subsampling1DLayer.Builder
-
- Builder(SubsamplingLayer.PoolingType) - Constructor for class org.deeplearning4j.nn.conf.layers.Subsampling1DLayer.Builder
-
- Builder(PoolingType) - Constructor for class org.deeplearning4j.nn.conf.layers.Subsampling1DLayer.Builder
-
- Builder() - Constructor for class org.deeplearning4j.nn.conf.layers.Subsampling1DLayer.Builder
-
- Builder(PoolingType, int, int, int) - Constructor for class org.deeplearning4j.nn.conf.layers.Subsampling1DLayer.Builder
-
- Builder(SubsamplingLayer.PoolingType, int, int, int) - Constructor for class org.deeplearning4j.nn.conf.layers.Subsampling1DLayer.Builder
-
- Builder(Subsampling3DLayer.PoolingType, int[], int[]) - Constructor for class org.deeplearning4j.nn.conf.layers.Subsampling3DLayer.Builder
-
- Builder(Subsampling3DLayer.PoolingType, int[]) - Constructor for class org.deeplearning4j.nn.conf.layers.Subsampling3DLayer.Builder
-
- Builder(Subsampling3DLayer.PoolingType, int[], int[], int[]) - Constructor for class org.deeplearning4j.nn.conf.layers.Subsampling3DLayer.Builder
-
- Builder(PoolingType, int[]) - Constructor for class org.deeplearning4j.nn.conf.layers.Subsampling3DLayer.Builder
-
- Builder(PoolingType, int[], int[], int[]) - Constructor for class org.deeplearning4j.nn.conf.layers.Subsampling3DLayer.Builder
-
- Builder(int[], int[], int[]) - Constructor for class org.deeplearning4j.nn.conf.layers.Subsampling3DLayer.Builder
-
- Builder(int[], int[]) - Constructor for class org.deeplearning4j.nn.conf.layers.Subsampling3DLayer.Builder
-
- Builder(int...) - Constructor for class org.deeplearning4j.nn.conf.layers.Subsampling3DLayer.Builder
-
- Builder(Subsampling3DLayer.PoolingType) - Constructor for class org.deeplearning4j.nn.conf.layers.Subsampling3DLayer.Builder
-
- Builder(PoolingType) - Constructor for class org.deeplearning4j.nn.conf.layers.Subsampling3DLayer.Builder
-
- Builder(SubsamplingLayer.PoolingType, int[], int[]) - Constructor for class org.deeplearning4j.nn.conf.layers.SubsamplingLayer.Builder
-
- Builder(SubsamplingLayer.PoolingType, int[]) - Constructor for class org.deeplearning4j.nn.conf.layers.SubsamplingLayer.Builder
-
- Builder(SubsamplingLayer.PoolingType, int[], int[], int[]) - Constructor for class org.deeplearning4j.nn.conf.layers.SubsamplingLayer.Builder
-
- Builder(PoolingType, int[]) - Constructor for class org.deeplearning4j.nn.conf.layers.SubsamplingLayer.Builder
-
- Builder(PoolingType, int[], int[], int[]) - Constructor for class org.deeplearning4j.nn.conf.layers.SubsamplingLayer.Builder
-
- Builder(int[], int[], int[]) - Constructor for class org.deeplearning4j.nn.conf.layers.SubsamplingLayer.Builder
-
- Builder(int[], int[]) - Constructor for class org.deeplearning4j.nn.conf.layers.SubsamplingLayer.Builder
-
- Builder(int...) - Constructor for class org.deeplearning4j.nn.conf.layers.SubsamplingLayer.Builder
-
- Builder(SubsamplingLayer.PoolingType) - Constructor for class org.deeplearning4j.nn.conf.layers.SubsamplingLayer.Builder
-
- Builder(PoolingType) - Constructor for class org.deeplearning4j.nn.conf.layers.SubsamplingLayer.Builder
-
- Builder(int) - Constructor for class org.deeplearning4j.nn.conf.layers.Upsampling1D.Builder
-
- Builder(int) - Constructor for class org.deeplearning4j.nn.conf.layers.Upsampling2D.Builder
-
- Builder(int) - Constructor for class org.deeplearning4j.nn.conf.layers.Upsampling3D.Builder
-
- Builder() - Constructor for class org.deeplearning4j.nn.conf.layers.variational.CompositeReconstructionDistribution.Builder
-
- Builder() - Constructor for class org.deeplearning4j.nn.conf.layers.variational.VariationalAutoencoder.Builder
-
- Builder(int) - Constructor for class org.deeplearning4j.nn.conf.layers.ZeroPadding1DLayer.Builder
-
- Builder(int, int) - Constructor for class org.deeplearning4j.nn.conf.layers.ZeroPadding1DLayer.Builder
-
- Builder(int[]) - Constructor for class org.deeplearning4j.nn.conf.layers.ZeroPadding1DLayer.Builder
-
- Builder(int) - Constructor for class org.deeplearning4j.nn.conf.layers.ZeroPadding3DLayer.Builder
-
- Builder(int, int, int) - Constructor for class org.deeplearning4j.nn.conf.layers.ZeroPadding3DLayer.Builder
-
Use same padding for left and right boundaries in depth, height and width.
- Builder(int, int, int, int, int, int) - Constructor for class org.deeplearning4j.nn.conf.layers.ZeroPadding3DLayer.Builder
-
Explicit padding of left and right boundaries in depth, height and width dimensions
- Builder(int[]) - Constructor for class org.deeplearning4j.nn.conf.layers.ZeroPadding3DLayer.Builder
-
- Builder(int, int) - Constructor for class org.deeplearning4j.nn.conf.layers.ZeroPaddingLayer.Builder
-
- Builder(int, int, int, int) - Constructor for class org.deeplearning4j.nn.conf.layers.ZeroPaddingLayer.Builder
-
- Builder(int[]) - Constructor for class org.deeplearning4j.nn.conf.layers.ZeroPaddingLayer.Builder
-
- Builder(String, Class<?>, InputType, InputType) - Constructor for class org.deeplearning4j.nn.conf.memory.LayerMemoryReport.Builder
-
- Builder() - Constructor for class org.deeplearning4j.nn.conf.MultiLayerConfiguration.Builder
-
- Builder() - Constructor for class org.deeplearning4j.nn.conf.NeuralNetConfiguration.Builder
-
- Builder(NeuralNetConfiguration) - Constructor for class org.deeplearning4j.nn.conf.NeuralNetConfiguration.Builder
-
- Builder() - Constructor for class org.deeplearning4j.nn.conf.ocnn.OCNNOutputLayer.Builder
-
- builder() - Static method in class org.deeplearning4j.nn.transferlearning.FineTuneConfiguration
-
- Builder() - Constructor for class org.deeplearning4j.nn.transferlearning.FineTuneConfiguration.Builder
-
- Builder(MultiLayerNetwork) - Constructor for class org.deeplearning4j.nn.transferlearning.TransferLearning.Builder
-
Multilayer Network to tweak for transfer learning
- builder() - Static method in class org.deeplearning4j.nn.workspace.LayerWorkspaceMgr
-
- Builder() - Constructor for class org.deeplearning4j.nn.workspace.LayerWorkspaceMgr.Builder
-
- Builder(String) - Constructor for class org.deeplearning4j.optimize.listeners.checkpoint.CheckpointListener.Builder
-
- Builder(File) - Constructor for class org.deeplearning4j.optimize.listeners.checkpoint.CheckpointListener.Builder
-
- Builder() - Constructor for class org.deeplearning4j.optimize.listeners.PerformanceListener.Builder
-
- Builder() - Constructor for class org.deeplearning4j.optimize.Solver.Builder
-
- Builder(int) - Constructor for class org.deeplearning4j.optimize.solvers.accumulation.EncodedGradientsAccumulator.Builder
-
This
- Builder() - Constructor for class org.deeplearning4j.parallelism.MagicQueue.Builder
-
Deprecated.
- Builder(Model) - Constructor for class org.deeplearning4j.parallelism.ParallelInference.Builder
-
- Builder(T) - Constructor for class org.deeplearning4j.parallelism.ParallelWrapper.Builder
-
Build ParallelWrapper for MultiLayerNetwork
- Builder() - Constructor for class org.deeplearning4j.perf.listener.SystemPolling.Builder
-
- Builder() - Constructor for class org.deeplearning4j.plot.BarnesHutTsne.Builder
-
- Builder() - Constructor for class org.deeplearning4j.plot.Tsne.Builder
-
- Builder() - Constructor for class org.deeplearning4j.spark.api.stats.CommonSparkTrainingStats.Builder
-
- Builder(int) - Constructor for class org.deeplearning4j.spark.impl.paramavg.ParameterAveragingTrainingMaster.Builder
-
Same as #Builder(Integer, int) but automatically set number of workers based on JavaSparkContext.defaultParallelism()
- Builder(Integer, int) - Constructor for class org.deeplearning4j.spark.impl.paramavg.ParameterAveragingTrainingMaster.Builder
-
Create a builder, where the following number of workers (Spark executors * number of threads per executor) are
being used.
Note: this should match the configuration of the cluster.
- Builder() - Constructor for class org.deeplearning4j.spark.models.embeddings.glove.GloveParam.Builder
-
- Builder() - Constructor for class org.deeplearning4j.spark.models.embeddings.word2vec.Word2Vec.Builder
-
Creates Builder instance with default parameters set.
- Builder(VectorsConfiguration) - Constructor for class org.deeplearning4j.spark.models.embeddings.word2vec.Word2Vec.Builder
-
Uses VectorsConfiguration bean to initialize Word2Vec model parameters
- Builder() - Constructor for class org.deeplearning4j.spark.models.embeddings.word2vec.Word2VecParam.Builder
-
Deprecated.
- Builder() - Constructor for class org.deeplearning4j.spark.models.sequencevectors.SparkSequenceVectors.Builder
-
Deprecated.
- Builder(VoidConfiguration) - Constructor for class org.deeplearning4j.spark.models.sequencevectors.SparkSequenceVectors.Builder
-
- Builder(VoidConfiguration, VectorsConfiguration) - Constructor for class org.deeplearning4j.spark.models.sequencevectors.SparkSequenceVectors.Builder
-
- Builder() - Constructor for class org.deeplearning4j.spark.models.word2vec.SparkWord2Vec.Builder
-
Deprecated.
- Builder(VoidConfiguration) - Constructor for class org.deeplearning4j.spark.models.word2vec.SparkWord2Vec.Builder
-
- Builder(VoidConfiguration, VectorsConfiguration) - Constructor for class org.deeplearning4j.spark.models.word2vec.SparkWord2Vec.Builder
-
- Builder(int) - Constructor for class org.deeplearning4j.spark.parameterserver.training.SharedTrainingMaster.Builder
-
- Builder(VoidConfiguration, int) - Constructor for class org.deeplearning4j.spark.parameterserver.training.SharedTrainingMaster.Builder
-
- Builder(double, int) - Constructor for class org.deeplearning4j.spark.parameterserver.training.SharedTrainingMaster.Builder
-
- Builder(VoidConfiguration, double, int) - Constructor for class org.deeplearning4j.spark.parameterserver.training.SharedTrainingMaster.Builder
-
- Builder(VoidConfiguration, Integer, double, int) - Constructor for class org.deeplearning4j.spark.parameterserver.training.SharedTrainingMaster.Builder
-
- Builder() - Constructor for class org.deeplearning4j.streaming.routes.CamelKafkaRouteBuilder.Builder
-
- Builder() - Constructor for class org.deeplearning4j.text.documentiterator.BasicLabelAwareIterator.Builder
-
This method should stay protected, since it's only viable for testing purposes
- Builder(SentenceIterator) - Constructor for class org.deeplearning4j.text.documentiterator.BasicLabelAwareIterator.Builder
-
We assume that each sentence in this iterator is separate document/paragraph
- Builder(DocumentIterator) - Constructor for class org.deeplearning4j.text.documentiterator.BasicLabelAwareIterator.Builder
-
We assume that each inputStream in this iterator is separate document/paragraph
- Builder(LabelAwareSentenceIterator) - Constructor for class org.deeplearning4j.text.documentiterator.BasicLabelAwareIterator.Builder
-
We assume that each sentence in this iterator is separate document/paragraph.
- Builder(LabelAwareDocumentIterator) - Constructor for class org.deeplearning4j.text.documentiterator.BasicLabelAwareIterator.Builder
-
We assume that each inputStream in this iterator is separate document/paragraph
Labels will be converted into LabelledDocument format
- Builder(LabelAwareIterator) - Constructor for class org.deeplearning4j.text.documentiterator.BasicLabelAwareIterator.Builder
-
- Builder() - Constructor for class org.deeplearning4j.text.documentiterator.FileLabelAwareIterator.Builder
-
- Builder() - Constructor for class org.deeplearning4j.text.documentiterator.FilenamesLabelAwareIterator.Builder
-
- Builder() - Constructor for class org.deeplearning4j.text.sentenceiterator.AggregatingSentenceIterator.Builder
-
- Builder(SentenceIterator) - Constructor for class org.deeplearning4j.text.sentenceiterator.PrefetchingSentenceIterator.Builder
-
Deprecated.
- Builder(InputStream) - Constructor for class org.deeplearning4j.text.sentenceiterator.StreamLineIterator.Builder
-
- Builder(DocumentIterator) - Constructor for class org.deeplearning4j.text.sentenceiterator.StreamLineIterator.Builder
-
- Builder() - Constructor for class org.deeplearning4j.ui.api.Style.Builder
-
- Builder(String, StyleChart) - Constructor for class org.deeplearning4j.ui.components.chart.Chart.Builder
-
- Builder(String, StyleChart) - Constructor for class org.deeplearning4j.ui.components.chart.ChartHistogram.Builder
-
- Builder(String, StyleChart) - Constructor for class org.deeplearning4j.ui.components.chart.ChartHorizontalBar.Builder
-
- Builder(String, StyleChart) - Constructor for class org.deeplearning4j.ui.components.chart.ChartLine.Builder
-
- Builder(String, StyleChart) - Constructor for class org.deeplearning4j.ui.components.chart.ChartScatter.Builder
-
- Builder(String, StyleChart) - Constructor for class org.deeplearning4j.ui.components.chart.ChartStackedArea.Builder
-
- Builder(String, StyleChart) - Constructor for class org.deeplearning4j.ui.components.chart.ChartTimeline.Builder
-
- Builder() - Constructor for class org.deeplearning4j.ui.components.chart.style.StyleChart.Builder
-
- Builder() - Constructor for class org.deeplearning4j.ui.components.component.style.StyleDiv.Builder
-
- Builder(StyleAccordion) - Constructor for class org.deeplearning4j.ui.components.decorator.DecoratorAccordion.Builder
-
- Builder(String, StyleAccordion) - Constructor for class org.deeplearning4j.ui.components.decorator.DecoratorAccordion.Builder
-
- Builder() - Constructor for class org.deeplearning4j.ui.components.decorator.style.StyleAccordion.Builder
-
- Builder(StyleTable) - Constructor for class org.deeplearning4j.ui.components.table.ComponentTable.Builder
-
- Builder() - Constructor for class org.deeplearning4j.ui.components.table.style.StyleTable.Builder
-
- Builder(String, StyleText) - Constructor for class org.deeplearning4j.ui.components.text.ComponentText.Builder
-
- Builder() - Constructor for class org.deeplearning4j.ui.components.text.style.StyleText.Builder
-
- Builder() - Constructor for class org.deeplearning4j.ui.stats.impl.DefaultStatsUpdateConfiguration.Builder
-
- Builder() - Constructor for class org.deeplearning4j.ui.storage.mapdb.MapDBStatsStorage.Builder
-
- Builder(File) - Constructor for class org.deeplearning4j.ui.storage.mapdb.MapDBStatsStorage.Builder
-
- Builder() - Constructor for class org.deeplearning4j.ui.UiConnectionInfo.Builder
-
- Builder(INDArray) - Constructor for class org.deeplearning4j.ui.weights.HistogramBin.Builder
-
Build Histogram Builder instance for specified array
- buildExtendedLookupTable() - Method in class org.deeplearning4j.models.word2vec.wordstore.VocabConstructor
-
Placeholder for future implementation
- buildExtendedVocabulary() - Method in class org.deeplearning4j.models.word2vec.wordstore.VocabConstructor
-
Placeholder for future implementation
- buildFromData(List<DataPoint>) - Static method in class org.deeplearning4j.clustering.vptree.VPTree
-
Create an ndarray
from the datapoints
- buildGraphInfo(MultiLayerConfiguration) - Static method in class org.deeplearning4j.ui.module.train.TrainModuleUtils
-
- buildGraphInfo(ComputationGraphConfiguration) - Static method in class org.deeplearning4j.ui.module.train.TrainModuleUtils
-
- buildGraphInfo(NeuralNetConfiguration) - Static method in class org.deeplearning4j.ui.module.train.TrainModuleUtils
-
- buildJointVocabulary(boolean, boolean) - Method in class org.deeplearning4j.models.word2vec.wordstore.VocabConstructor
-
This method scans all sources passed through builder, and returns all words as vocab.
- buildMergedVocabulary(WordVectors, boolean) - Method in class org.deeplearning4j.models.word2vec.wordstore.VocabConstructor
-
This method transfers existing WordVectors model into current one
- buildMergedVocabulary(VocabCache<T>, boolean) - Method in class org.deeplearning4j.models.word2vec.wordstore.VocabConstructor
-
This method transfers existing vocabulary into current one
Please note: this method expects source vocabulary has Huffman tree indexes applied
- buildModel() - Method in class org.deeplearning4j.nn.modelimport.keras.utils.KerasModelBuilder
-
- buildNetworkSnapshot() - Method in class org.deeplearning4j.spark.models.sequencevectors.primitives.ExtraCounter
-
- buildNode(List<Byte>, List<Integer>, int, int) - Static method in class org.deeplearning4j.models.word2vec.wordstore.VocabularyHolder
-
- buildSequential() - Method in class org.deeplearning4j.nn.modelimport.keras.utils.KerasModelBuilder
-
- buildShallowVocabCache(Counter<Long>) - Method in class org.deeplearning4j.spark.models.sequencevectors.SparkSequenceVectors
-
This method builds shadow vocabulary and huffman tree
- buildTree(INDArray) - Method in class org.deeplearning4j.clustering.randomprojection.RPTree
-
Build the tree with the given input data
- buildTree(RPTree, RPNode, RPHyperPlanes, INDArray, int, int, String) - Static method in class org.deeplearning4j.clustering.randomprojection.RPUtils
-
Initialize the tree given the input parameters
- buildTree(int[]) - Method in class org.deeplearning4j.graph.models.deepwalk.GraphHuffman
-
Build the Huffman tree given an array of vertex degrees
- buildTree(int[]) - Method in class org.deeplearning4j.models.sequencevectors.graph.huffman.GraphHuffman
-
Build the Huffman tree given an array of vertex degrees
- buildTree(TreebankNode, Pair<String, MultiDimensionalMap<Integer, Integer, String>>, List<String>) - Static method in class org.deeplearning4j.text.corpora.treeparser.TreeFactory
-
Builds a tree recursively
adding the children as necessary
- buildTree(TreebankNode) - Static method in class org.deeplearning4j.text.corpora.treeparser.TreeFactory
-
Builds a tree recursively
adding the children as necessary
- buildUnknownWordDictionary(String, String, String) - Method in class com.atilika.kuromoji.compile.DictionaryCompilerBase
-
- buildVocab() - Method in class org.deeplearning4j.bagofwords.vectorizer.BaseTextVectorizer
-
- buildVocab() - Method in class org.deeplearning4j.models.sequencevectors.SequenceVectors
-
Builds vocabulary from provided SequenceIterator instance
- buildVocabCache() - Method in class org.deeplearning4j.spark.text.functions.TextPipeline
-
- buildVocabWordListRDD() - Method in class org.deeplearning4j.spark.text.functions.TextPipeline
-
- bypassMode - Variable in class org.deeplearning4j.optimize.solvers.accumulation.EncodedGradientsAccumulator
-
- bypassMode - Variable in class org.deeplearning4j.optimize.solvers.accumulation.FancyBlockingQueue
-
- bypassMode - Variable in class org.deeplearning4j.spark.parameterserver.networking.SilentTrainingDriver
-
- bypassMode(boolean) - Method in class org.deeplearning4j.spark.parameterserver.networking.SilentTrainingDriver
-
- ByteBufferIO - Class in com.atilika.kuromoji.io
-
- ByteBufferIO() - Constructor for class com.atilika.kuromoji.io.ByteBufferIO
-
- bytes() - Method in class org.deeplearning4j.ui.stats.sbe.StorageMetaDataDecoder.ExtraMetaDataBytesDecoder
-
- bytes(byte) - Method in class org.deeplearning4j.ui.stats.sbe.StorageMetaDataEncoder.ExtraMetaDataBytesEncoder
-
- bytes() - Method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder.DataSetMetaDataBytesDecoder.MetaDataBytesDecoder
-
- bytes(byte) - Method in class org.deeplearning4j.ui.stats.sbe.UpdateEncoder.DataSetMetaDataBytesEncoder.MetaDataBytesEncoder
-
- bytesId() - Static method in class org.deeplearning4j.ui.stats.sbe.StorageMetaDataDecoder.ExtraMetaDataBytesDecoder
-
- bytesId() - Static method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder.DataSetMetaDataBytesDecoder.MetaDataBytesDecoder
-
- bytesMaxValue() - Static method in class org.deeplearning4j.ui.stats.sbe.StorageMetaDataDecoder.ExtraMetaDataBytesDecoder
-
- bytesMaxValue() - Static method in class org.deeplearning4j.ui.stats.sbe.StorageMetaDataEncoder.ExtraMetaDataBytesEncoder
-
- bytesMaxValue() - Static method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder.DataSetMetaDataBytesDecoder.MetaDataBytesDecoder
-
- bytesMaxValue() - Static method in class org.deeplearning4j.ui.stats.sbe.UpdateEncoder.DataSetMetaDataBytesEncoder.MetaDataBytesEncoder
-
- bytesMetaAttribute(MetaAttribute) - Static method in class org.deeplearning4j.ui.stats.sbe.StorageMetaDataDecoder.ExtraMetaDataBytesDecoder
-
- bytesMetaAttribute(MetaAttribute) - Static method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder.DataSetMetaDataBytesDecoder.MetaDataBytesDecoder
-
- bytesMinValue() - Static method in class org.deeplearning4j.ui.stats.sbe.StorageMetaDataDecoder.ExtraMetaDataBytesDecoder
-
- bytesMinValue() - Static method in class org.deeplearning4j.ui.stats.sbe.StorageMetaDataEncoder.ExtraMetaDataBytesEncoder
-
- bytesMinValue() - Static method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder.DataSetMetaDataBytesDecoder.MetaDataBytesDecoder
-
- bytesMinValue() - Static method in class org.deeplearning4j.ui.stats.sbe.UpdateEncoder.DataSetMetaDataBytesEncoder.MetaDataBytesEncoder
-
- bytesNullValue() - Static method in class org.deeplearning4j.ui.stats.sbe.StorageMetaDataDecoder.ExtraMetaDataBytesDecoder
-
- bytesNullValue() - Static method in class org.deeplearning4j.ui.stats.sbe.StorageMetaDataEncoder.ExtraMetaDataBytesEncoder
-
- bytesNullValue() - Static method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder.DataSetMetaDataBytesDecoder.MetaDataBytesDecoder
-
- bytesNullValue() - Static method in class org.deeplearning4j.ui.stats.sbe.UpdateEncoder.DataSetMetaDataBytesEncoder.MetaDataBytesEncoder
-
- c3x3reduce(int, int, double) - Static method in class org.deeplearning4j.zoo.model.helper.FaceNetHelper
-
- c5x5reduce(int, int, double) - Static method in class org.deeplearning4j.zoo.model.helper.FaceNetHelper
-
- cache - Variable in class org.deeplearning4j.bagofwords.vectorizer.Builder
-
Deprecated.
- cache(VocabCache) - Method in class org.deeplearning4j.bagofwords.vectorizer.Builder
-
Deprecated.
- cache(VocabCache<T>) - Method in class org.deeplearning4j.models.embeddings.inmemory.InMemoryLookupTable.Builder
-
- cache(VocabCache<T>) - Method in class org.deeplearning4j.models.glove.GloveWeightLookupTable.Builder
-
Deprecated.
- cache - Variable in class org.deeplearning4j.text.sentenceiterator.FileSentenceIterator
-
- CACHE_MODE_ALL_ZEROS - Static variable in class org.deeplearning4j.nn.conf.memory.MemoryReport
-
A simple Map containing all zeros for each CacheMode key
- CacheableExtractableDataSetFetcher - Class in org.deeplearning4j.datasets.fetchers
-
Abstract class for enabling dataset downloading and local caching.
- CacheableExtractableDataSetFetcher() - Constructor for class org.deeplearning4j.datasets.fetchers.CacheableExtractableDataSetFetcher
-
- cachedFwdPass - Variable in class org.deeplearning4j.nn.layers.recurrent.GravesLSTM
-
- cachedFwdPass - Variable in class org.deeplearning4j.nn.layers.recurrent.LSTM
-
- cachedPassBackward - Variable in class org.deeplearning4j.nn.layers.recurrent.GravesBidirectionalLSTM
-
- cachedPassForward - Variable in class org.deeplearning4j.nn.layers.recurrent.GravesBidirectionalLSTM
-
- cacheMemory(long, long) - Method in class org.deeplearning4j.nn.conf.memory.LayerMemoryReport.Builder
-
Reports the cached/cacheable memory requirements.
- cacheMemory(Map<CacheMode, Long>, Map<CacheMode, Long>) - Method in class org.deeplearning4j.nn.conf.memory.LayerMemoryReport.Builder
-
Reports the cached/cacheable memory requirements.
- CacheMode - Enum in org.deeplearning4j.nn.conf
-
- cacheMode - Variable in class org.deeplearning4j.nn.conf.ComputationGraphConfiguration
-
- cacheMode - Variable in class org.deeplearning4j.nn.conf.MultiLayerConfiguration.Builder
-
- cacheMode(CacheMode) - Method in class org.deeplearning4j.nn.conf.MultiLayerConfiguration.Builder
-
This method defines how/if preOutput cache is handled:
NONE: cache disabled (default value)
HOST: Host memory will be used
DEVICE: GPU memory will be used (on CPU backends effect will be the same as for HOST)
- cacheMode - Variable in class org.deeplearning4j.nn.conf.MultiLayerConfiguration
-
- cacheMode - Variable in class org.deeplearning4j.nn.conf.NeuralNetConfiguration.Builder
-
- cacheMode(CacheMode) - Method in class org.deeplearning4j.nn.conf.NeuralNetConfiguration.Builder
-
This method defines how/if preOutput cache is handled:
NONE: cache disabled (default value)
HOST: Host memory will be used
DEVICE: GPU memory will be used (on CPU backends effect will be the same as for HOST)
- cacheMode - Variable in class org.deeplearning4j.nn.conf.NeuralNetConfiguration
-
- cacheMode - Variable in class org.deeplearning4j.nn.layers.AbstractLayer
-
- cacheMode - Variable in class org.deeplearning4j.nn.layers.variational.VariationalAutoencoder
-
- cacheModeMapFor(long) - Static method in class org.deeplearning4j.nn.conf.memory.MemoryReport
-
Get a map of CacheMode with all keys associated with the specified value
- calcBackpropGradients(boolean, boolean, INDArray...) - Method in class org.deeplearning4j.nn.graph.ComputationGraph
-
Do backprop (gradient calculation)
- calcBackpropGradients(INDArray, boolean, boolean, boolean) - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
-
Calculate gradients and errors.
- calcDistancesRelativeTo(INDArray, INDArray, INDArray) - Method in class org.deeplearning4j.clustering.vptree.VPTree
-
- calcDistancesRelativeTo(INDArray, INDArray) - Method in class org.deeplearning4j.clustering.vptree.VPTree
-
- calcL1(boolean) - Method in interface org.deeplearning4j.nn.api.Layer
-
Calculate the l1 regularization term
0.0 if regularization is not used.
- calcL1() - Method in class org.deeplearning4j.nn.graph.ComputationGraph
-
Calculate the L1 regularization term for all layers in the entire network.
- calcL1(boolean) - Method in class org.deeplearning4j.nn.layers.AbstractLayer
-
- calcL1(boolean) - Method in class org.deeplearning4j.nn.layers.ActivationLayer
-
- calcL1(boolean) - Method in class org.deeplearning4j.nn.layers.BaseLayer
-
- calcL1(boolean) - Method in class org.deeplearning4j.nn.layers.BasePretrainNetwork
-
- calcL1(boolean) - Method in class org.deeplearning4j.nn.layers.convolution.CnnLossLayer
-
- calcL1(boolean) - Method in class org.deeplearning4j.nn.layers.convolution.Cropping1DLayer
-
- calcL1(boolean) - Method in class org.deeplearning4j.nn.layers.convolution.Cropping2DLayer
-
- calcL1(boolean) - Method in class org.deeplearning4j.nn.layers.convolution.Cropping3DLayer
-
- calcL1(boolean) - Method in class org.deeplearning4j.nn.layers.convolution.SpaceToBatch
-
- calcL1(boolean) - Method in class org.deeplearning4j.nn.layers.convolution.SpaceToDepth
-
- calcL1(boolean) - Method in class org.deeplearning4j.nn.layers.convolution.subsampling.Subsampling3DLayer
-
- calcL1(boolean) - Method in class org.deeplearning4j.nn.layers.convolution.subsampling.SubsamplingLayer
-
- calcL1(boolean) - Method in class org.deeplearning4j.nn.layers.convolution.upsampling.Upsampling2D
-
- calcL1(boolean) - Method in class org.deeplearning4j.nn.layers.convolution.upsampling.Upsampling3D
-
- calcL1(boolean) - Method in class org.deeplearning4j.nn.layers.convolution.ZeroPadding1DLayer
-
- calcL1(boolean) - Method in class org.deeplearning4j.nn.layers.convolution.ZeroPadding3DLayer
-
- calcL1(boolean) - Method in class org.deeplearning4j.nn.layers.convolution.ZeroPaddingLayer
-
- calcL1(boolean) - Method in class org.deeplearning4j.nn.layers.DropoutLayer
-
- calcL1(boolean) - Method in class org.deeplearning4j.nn.layers.FrozenLayer
-
- calcL1(boolean) - Method in class org.deeplearning4j.nn.layers.FrozenLayerWithBackprop
-
- calcL1(boolean) - Method in class org.deeplearning4j.nn.layers.LossLayer
-
- calcL1(boolean) - Method in class org.deeplearning4j.nn.layers.normalization.BatchNormalization
-
- calcL1(boolean) - Method in class org.deeplearning4j.nn.layers.normalization.LocalResponseNormalization
-
- calcL1(boolean) - Method in class org.deeplearning4j.nn.layers.pooling.GlobalPoolingLayer
-
- calcL1(boolean) - Method in class org.deeplearning4j.nn.layers.recurrent.BidirectionalLayer
-
- calcL1(boolean) - Method in class org.deeplearning4j.nn.layers.recurrent.RnnLossLayer
-
- calcL1(boolean) - Method in class org.deeplearning4j.nn.layers.variational.VariationalAutoencoder
-
- calcL1(boolean) - Method in class org.deeplearning4j.nn.layers.wrapper.BaseWrapperLayer
-
- calcL1(boolean) - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
-
- calcL2(boolean) - Method in interface org.deeplearning4j.nn.api.Layer
-
Calculate the l2 regularization term
0.0 if regularization is not used.
- calcL2() - Method in class org.deeplearning4j.nn.graph.ComputationGraph
-
Calculate the L2 regularization term for all layers in the entire network.
- calcL2(boolean) - Method in class org.deeplearning4j.nn.layers.AbstractLayer
-
- calcL2(boolean) - Method in class org.deeplearning4j.nn.layers.ActivationLayer
-
- calcL2(boolean) - Method in class org.deeplearning4j.nn.layers.BaseLayer
-
- calcL2(boolean) - Method in class org.deeplearning4j.nn.layers.BasePretrainNetwork
-
- calcL2(boolean) - Method in class org.deeplearning4j.nn.layers.convolution.CnnLossLayer
-
- calcL2(boolean) - Method in class org.deeplearning4j.nn.layers.convolution.Cropping1DLayer
-
- calcL2(boolean) - Method in class org.deeplearning4j.nn.layers.convolution.Cropping2DLayer
-
- calcL2(boolean) - Method in class org.deeplearning4j.nn.layers.convolution.Cropping3DLayer
-
- calcL2(boolean) - Method in class org.deeplearning4j.nn.layers.convolution.SpaceToBatch
-
- calcL2(boolean) - Method in class org.deeplearning4j.nn.layers.convolution.SpaceToDepth
-
- calcL2(boolean) - Method in class org.deeplearning4j.nn.layers.convolution.subsampling.Subsampling3DLayer
-
- calcL2(boolean) - Method in class org.deeplearning4j.nn.layers.convolution.subsampling.SubsamplingLayer
-
- calcL2(boolean) - Method in class org.deeplearning4j.nn.layers.convolution.upsampling.Upsampling2D
-
- calcL2(boolean) - Method in class org.deeplearning4j.nn.layers.convolution.upsampling.Upsampling3D
-
- calcL2(boolean) - Method in class org.deeplearning4j.nn.layers.convolution.ZeroPadding1DLayer
-
- calcL2(boolean) - Method in class org.deeplearning4j.nn.layers.convolution.ZeroPadding3DLayer
-
- calcL2(boolean) - Method in class org.deeplearning4j.nn.layers.convolution.ZeroPaddingLayer
-
- calcL2(boolean) - Method in class org.deeplearning4j.nn.layers.DropoutLayer
-
- calcL2(boolean) - Method in class org.deeplearning4j.nn.layers.FrozenLayer
-
- calcL2(boolean) - Method in class org.deeplearning4j.nn.layers.FrozenLayerWithBackprop
-
- calcL2(boolean) - Method in class org.deeplearning4j.nn.layers.LossLayer
-
- calcL2(boolean) - Method in class org.deeplearning4j.nn.layers.normalization.BatchNormalization
-
- calcL2(boolean) - Method in class org.deeplearning4j.nn.layers.normalization.LocalResponseNormalization
-
- calcL2(boolean) - Method in class org.deeplearning4j.nn.layers.pooling.GlobalPoolingLayer
-
- calcL2(boolean) - Method in class org.deeplearning4j.nn.layers.recurrent.BidirectionalLayer
-
- calcL2(boolean) - Method in class org.deeplearning4j.nn.layers.recurrent.RnnLossLayer
-
- calcL2(boolean) - Method in class org.deeplearning4j.nn.layers.variational.VariationalAutoencoder
-
- calcL2(boolean) - Method in class org.deeplearning4j.nn.layers.wrapper.BaseWrapperLayer
-
- calcL2(boolean) - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
-
- calculate(INDArray, int, double) - Method in class org.deeplearning4j.plot.Tsne
-
- calculateArea() - Method in class org.deeplearning4j.eval.curves.BaseCurve
-
- calculateArea(double[], double[]) - Method in class org.deeplearning4j.eval.curves.BaseCurve
-
- calculateAUC() - Method in class org.deeplearning4j.eval.curves.RocCurve
-
Calculate and return the area under ROC curve
- calculateAUC() - Method in class org.deeplearning4j.eval.ROC
-
Calculate the AUROC - Area Under ROC Curve
Utilizes trapezoidal integration internally
- calculateAUC(int) - Method in class org.deeplearning4j.eval.ROCBinary
-
Calculate the AUC - Area Under (ROC) Curve
Utilizes trapezoidal integration internally
- calculateAUC(int) - Method in class org.deeplearning4j.eval.ROCMultiClass
-
Calculate the AUC - Area Under ROC Curve
Utilizes trapezoidal integration internally
- calculateAUCPR() - Method in class org.deeplearning4j.eval.ROC
-
Calculate the area under the precision/recall curve - aka AUCPR
- calculateAUCPR(int) - Method in class org.deeplearning4j.eval.ROCBinary
-
Calculate the AUCPR - Area Under Curve - Precision Recall
Utilizes trapezoidal integration internally
- calculateAUCPR(int) - Method in class org.deeplearning4j.eval.ROCMultiClass
-
Calculate the AUPRC - Area Under Curve Precision Recall
Utilizes trapezoidal integration internally
- calculateAUPRC() - Method in class org.deeplearning4j.eval.curves.PrecisionRecallCurve
-
- calculateAverageAuc() - Method in class org.deeplearning4j.eval.ROCBinary
-
Macro-average AUC for all outcomes
- calculateAverageAUC() - Method in class org.deeplearning4j.eval.ROCMultiClass
-
Calculate the macro-average (one-vs-all) AUC for all classes
- calculateAverageAUCPR() - Method in class org.deeplearning4j.eval.ROCBinary
-
- calculateAverageAUCPR() - Method in class org.deeplearning4j.eval.ROCMultiClass
-
Calculate the macro-average (one-vs-all) AUCPR (area under precision recall curve) for all classes
- calculateGradients(INDArray, INDArray, INDArray, INDArray) - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
-
Calculate parameter gradients and input activation gradients given the input and labels
- calculateIndices() - Method in class org.deeplearning4j.nn.graph.ComputationGraph
-
Calculate the indices needed for the network:
(a) topological sort order
(b) Map: vertex index -> vertex name
(c) Map: vertex name -> vertex index
- calculateProb(int, int) - Method in class org.deeplearning4j.graph.models.embeddings.InMemoryGraphLookupTable
-
Calculate the probability of the second vertex given the first vertex
i.e., P(v_second | v_first)
- calculateScore(T) - Method in class org.deeplearning4j.earlystopping.scorecalc.base.BaseIEvaluationScoreCalculator
-
- calculateScore(T) - Method in class org.deeplearning4j.earlystopping.scorecalc.base.BaseScoreCalculator
-
- calculateScore(ComputationGraph) - Method in class org.deeplearning4j.earlystopping.scorecalc.DataSetLossCalculatorCG
-
Deprecated.
- calculateScore(T) - Method in interface org.deeplearning4j.earlystopping.scorecalc.ScoreCalculator
-
Calculate the score for the given MultiLayerNetwork
- calculateScore(int, int) - Method in class org.deeplearning4j.graph.models.embeddings.InMemoryGraphLookupTable
-
Calculate score.
- calculateScore(MultiLayerNetwork) - Method in class org.deeplearning4j.spark.earlystopping.SparkDataSetLossCalculator
-
- calculateScore(ComputationGraph) - Method in class org.deeplearning4j.spark.earlystopping.SparkLossCalculatorComputationGraph
-
- calculateScore(JavaRDD<DataSet>, boolean) - Method in class org.deeplearning4j.spark.impl.graph.SparkComputationGraph
-
Calculate the score for all examples in the provided JavaRDD<DataSet>, either by summing
or averaging over the entire data set.
- calculateScore(JavaRDD<DataSet>, boolean, int) - Method in class org.deeplearning4j.spark.impl.graph.SparkComputationGraph
-
Calculate the score for all examples in the provided JavaRDD<DataSet>, either by summing
or averaging over the entire data set.
- calculateScore(RDD<DataSet>, boolean) - Method in class org.deeplearning4j.spark.impl.multilayer.SparkDl4jMultiLayer
-
- calculateScore(JavaRDD<DataSet>, boolean) - Method in class org.deeplearning4j.spark.impl.multilayer.SparkDl4jMultiLayer
-
Calculate the score for all examples in the provided JavaRDD<DataSet>, either by summing
or averaging over the entire data set.
- calculateScore(JavaRDD<DataSet>, boolean, int) - Method in class org.deeplearning4j.spark.impl.multilayer.SparkDl4jMultiLayer
-
Calculate the score for all examples in the provided JavaRDD<DataSet>, either by summing
or averaging over the entire data set.
- calculateScoreMultiDataSet(JavaRDD<MultiDataSet>, boolean) - Method in class org.deeplearning4j.spark.impl.graph.SparkComputationGraph
-
Calculate the score for all examples in the provided JavaRDD<MultiDataSet>, either by summing
or averaging over the entire data set.
- calculateScoreMultiDataSet(JavaRDD<MultiDataSet>, boolean, int) - Method in class org.deeplearning4j.spark.impl.graph.SparkComputationGraph
-
Calculate the score for all examples in the provided JavaRDD<MultiDataSet>, either by summing
or averaging over the entire data set.
- call() - Method in class org.deeplearning4j.clustering.vptree.VPTree.NodeBuilder
-
- call(DataSet) - Method in interface org.deeplearning4j.datasets.iterator.callbacks.DataSetCallback
-
- call(MultiDataSet) - Method in interface org.deeplearning4j.datasets.iterator.callbacks.DataSetCallback
-
- call(File) - Method in class org.deeplearning4j.datasets.iterator.callbacks.DataSetDeserializer
-
- call(DataSet) - Method in class org.deeplearning4j.datasets.iterator.callbacks.DefaultCallback
-
- call(MultiDataSet) - Method in class org.deeplearning4j.datasets.iterator.callbacks.DefaultCallback
-
- call(File) - Method in interface org.deeplearning4j.datasets.iterator.callbacks.FileCallback
-
- call(DataSet) - Method in class org.deeplearning4j.datasets.iterator.callbacks.InterleavedDataSetCallback
-
- call(MultiDataSet) - Method in class org.deeplearning4j.datasets.iterator.callbacks.InterleavedDataSetCallback
-
- call() - Method in class org.deeplearning4j.models.paragraphvectors.ParagraphVectors.BlindInferenceCallable
-
- call() - Method in class org.deeplearning4j.models.paragraphvectors.ParagraphVectors.InferenceCallable
-
- call(EvaluativeListener, Model, long, IEvaluation[]) - Method in interface org.deeplearning4j.optimize.listeners.callbacks.EvaluationCallback
-
- call(EvaluativeListener, Model, long, IEvaluation[]) - Method in class org.deeplearning4j.optimize.listeners.callbacks.ModelSavingCallback
-
- call(Integer, Iterator<DataSet>) - Method in class org.deeplearning4j.spark.data.BatchAndExportDataSetsFunction
-
- call(Integer, Iterator<MultiDataSet>) - Method in class org.deeplearning4j.spark.data.BatchAndExportMultiDataSetsFunction
-
- call(Iterator<DataSet>) - Method in class org.deeplearning4j.spark.data.DataSetExportFunction
-
- call(Iterator<MultiDataSet>) - Method in class org.deeplearning4j.spark.data.MultiDataSetExportFunction
-
- call(String) - Method in class org.deeplearning4j.spark.data.PathToDataSetFunction
-
- call(String) - Method in class org.deeplearning4j.spark.data.PathToMultiDataSetFunction
-
- call(Tuple2<Text, BytesWritable>) - Method in class org.deeplearning4j.spark.datavec.DataVecByteDataSetFunction
-
- call(List<Writable>) - Method in class org.deeplearning4j.spark.datavec.DataVecDataSetFunction
-
- call(List<List<Writable>>) - Method in class org.deeplearning4j.spark.datavec.DataVecSequenceDataSetFunction
-
- call(Tuple2<List<List<Writable>>, List<List<Writable>>>) - Method in class org.deeplearning4j.spark.datavec.DataVecSequencePairDataSetFunction
-
- call(Iterator<String>) - Method in class org.deeplearning4j.spark.datavec.export.StringToDataSetExportFunction
-
- call(DataVecRecords) - Method in class org.deeplearning4j.spark.datavec.iterator.RRMDSIFunction
-
- call(String) - Method in class org.deeplearning4j.spark.datavec.RecordReaderFunction
-
- call(INDArray, INDArray) - Method in class org.deeplearning4j.spark.impl.common.Add
-
- call(Integer, Iterator<T>) - Method in class org.deeplearning4j.spark.impl.common.CountPartitionsFunction
-
- call(PortableDataStream) - Method in class org.deeplearning4j.spark.impl.common.LoadSerializedDataSetFunction
-
- call(Tuple2<Integer, Double>, Tuple2<Integer, Double>) - Method in class org.deeplearning4j.spark.impl.common.reduce.IntDoubleReduceFunction
-
- call(Integer, Iterator<T>) - Method in class org.deeplearning4j.spark.impl.common.repartition.AssignIndexFunction
-
Deprecated.
- call(Iterator<Tuple2<K, INDArray>>) - Method in class org.deeplearning4j.spark.impl.common.score.BaseVaeScoreWithKeyFunctionAdapter
-
- call(Integer, Iterator<T>) - Method in class org.deeplearning4j.spark.impl.common.SplitPartitionsFunction
-
- call(Integer, Iterator<Tuple2<T, U>>) - Method in class org.deeplearning4j.spark.impl.common.SplitPartitionsFunction2
-
- call(DataSet) - Method in class org.deeplearning4j.spark.impl.graph.dataset.DataSetToMultiDataSetFn
-
- call(Tuple2<K, DataSet>) - Method in class org.deeplearning4j.spark.impl.graph.dataset.PairDataSetToMultiDataSetFn
-
- call(Tuple2<K, INDArray[]>) - Method in class org.deeplearning4j.spark.impl.graph.scoring.ArrayPairToPair
-
- call(Tuple2<K, INDArray>) - Method in class org.deeplearning4j.spark.impl.graph.scoring.PairToArrayPair
-
- call(T[], T[]) - Method in class org.deeplearning4j.spark.impl.multilayer.evaluation.IEvaluateAggregateFunction
-
- call(T[], T[]) - Method in class org.deeplearning4j.spark.impl.multilayer.evaluation.IEvaluationReduceFunction
-
- call(Tuple2<T, INDArray>) - Method in class org.deeplearning4j.spark.impl.multilayer.scoring.SingleToPairFunction
-
- call(ParameterAveragingAggregationTuple, ParameterAveragingTrainingResult) - Method in class org.deeplearning4j.spark.impl.paramavg.aggregator.ParameterAveragingElementAddFunction
-
- call(ParameterAveragingAggregationTuple, ParameterAveragingAggregationTuple) - Method in class org.deeplearning4j.spark.impl.paramavg.aggregator.ParameterAveragingElementCombineFunction
-
- call(Pair<List<String>, AtomicLong>) - Method in class org.deeplearning4j.spark.models.embeddings.glove.cooccurrences.CoOccurrenceCalculator
-
- call(CounterMap<String, String>, CounterMap<String, String>) - Method in class org.deeplearning4j.spark.models.embeddings.glove.cooccurrences.CoOccurrenceCounts
-
- call(Triple<VocabWord, VocabWord, Double>) - Method in class org.deeplearning4j.spark.models.embeddings.glove.GlovePerformer
-
- call(Triple<String, String, Double>) - Method in class org.deeplearning4j.spark.models.embeddings.glove.VocabWordPairs
-
- call(Iterator<Tuple2<List<VocabWord>, Long>>) - Method in class org.deeplearning4j.spark.models.embeddings.word2vec.FirstIterationFunctionAdapter
-
- call(Map.Entry<VocabWord, INDArray>) - Method in class org.deeplearning4j.spark.models.embeddings.word2vec.MapToPairFunction
-
- call(Word2VecFuncCall) - Method in class org.deeplearning4j.spark.models.embeddings.word2vec.SentenceBatch
-
Deprecated.
- call(Pair<List<VocabWord>, AtomicLong>) - Method in class org.deeplearning4j.spark.models.embeddings.word2vec.Word2VecPerformer
-
Deprecated.
- call(Pair<List<VocabWord>, AtomicLong>) - Method in class org.deeplearning4j.spark.models.embeddings.word2vec.Word2VecPerformerVoid
-
Deprecated.
- call(Tuple2<List<VocabWord>, Long>) - Method in class org.deeplearning4j.spark.models.embeddings.word2vec.Word2VecSetup
-
Deprecated.
- call(LabelledDocument) - Method in class org.deeplearning4j.spark.models.paragraphvectors.functions.DocumentSequenceConvertFunction
-
- call(Tuple2<String, String>) - Method in class org.deeplearning4j.spark.models.paragraphvectors.functions.KeySequenceConvertFunction
-
- call(Sequence<T>) - Method in class org.deeplearning4j.spark.models.sequencevectors.functions.CountFunction
-
- call(T) - Method in class org.deeplearning4j.spark.models.sequencevectors.functions.DistributedFunction
-
- call(T) - Method in class org.deeplearning4j.spark.models.sequencevectors.functions.ExportFunction
-
- call(Sequence<T>) - Method in class org.deeplearning4j.spark.models.sequencevectors.functions.ExtraCountFunction
-
- call(List<T>) - Method in class org.deeplearning4j.spark.models.sequencevectors.functions.ListSequenceConvertFunction
-
- call(Iterator<Sequence<T>>) - Method in class org.deeplearning4j.spark.models.sequencevectors.functions.PartitionTrainingFunction
-
- call(String) - Method in class org.deeplearning4j.spark.models.sequencevectors.functions.TokenizerFunction
-
- call(Sequence<T>) - Method in class org.deeplearning4j.spark.models.sequencevectors.functions.TrainingFunction
-
- call(SharedTrainingAccumulationTuple, SharedTrainingAccumulationTuple) - Method in class org.deeplearning4j.spark.parameterserver.accumulation.SharedTrainingAccumulationFunction
-
- call(SharedTrainingAccumulationTuple, SharedTrainingResult) - Method in class org.deeplearning4j.spark.parameterserver.accumulation.SharedTrainingAggregateFunction
-
- call(Integer, Iterator<AtomicLong>) - Method in class org.deeplearning4j.spark.text.functions.FoldBetweenPartitionFunction
-
- call(Integer, Iterator<AtomicLong>) - Method in class org.deeplearning4j.spark.text.functions.FoldWithinPartitionFunction
-
- call(Pair<List<String>, AtomicLong>) - Method in class org.deeplearning4j.spark.text.functions.GetSentenceCountFunction
-
- call(Iterator<?>) - Method in class org.deeplearning4j.spark.text.functions.MapPerPartitionVoidFunction
-
- call(AtomicLong, AtomicLong) - Method in class org.deeplearning4j.spark.text.functions.ReduceSentenceCount
-
- call(String) - Method in class org.deeplearning4j.spark.text.functions.TokenizerFunction
-
- call(List<String>) - Method in class org.deeplearning4j.spark.text.functions.UpdateWordFreqAccumulatorFunction
-
- call(Pair<List<String>, AtomicLong>) - Method in class org.deeplearning4j.spark.text.functions.WordsListToVocabWordsFunction
-
- call(T) - Method in class org.deeplearning4j.spark.util.BaseDoubleFlatMapFunctionAdaptee
-
- call(T) - Method in class org.deeplearning4j.spark.util.BasePairFlatMapFunctionAdaptee
-
- call(String) - Method in class org.deeplearning4j.spark.util.data.validation.ValidateDataSetFn
-
- call(String) - Method in class org.deeplearning4j.spark.util.data.validation.ValidateMultiDataSetFn
-
- call(ValidationResult, ValidationResult) - Method in class org.deeplearning4j.spark.util.data.validation.ValidationResultReduceFn
-
- callback - Variable in class org.deeplearning4j.datasets.iterator.AsyncDataSetIterator
-
- callback - Variable in class org.deeplearning4j.datasets.iterator.AsyncMultiDataSetIterator
-
- callback - Variable in class org.deeplearning4j.optimize.listeners.EvaluativeListener
-
This callback will be invoked after evaluation finished
- callback - Variable in class org.deeplearning4j.spark.parameterserver.iterators.MultiPdsIterator
-
- callback - Variable in class org.deeplearning4j.spark.parameterserver.iterators.PdsIterator
-
- camelContext(CamelContext) - Method in class org.deeplearning4j.streaming.routes.CamelKafkaRouteBuilder.Builder
-
- CamelKafkaRouteBuilder - Class in org.deeplearning4j.streaming.routes
-
A Camel Java DSL Router
- CamelKafkaRouteBuilder() - Constructor for class org.deeplearning4j.streaming.routes.CamelKafkaRouteBuilder
-
- CamelKafkaRouteBuilder.Builder - Class in org.deeplearning4j.streaming.routes
-
- candidates - Variable in class org.deeplearning4j.optimize.solvers.accumulation.BasicGradientsAccumulator
-
- canDoBackward() - Method in class org.deeplearning4j.nn.graph.vertex.BaseGraphVertex
-
- canDoBackward() - Method in class org.deeplearning4j.nn.graph.vertex.BaseWrapperVertex
-
- canDoBackward() - Method in interface org.deeplearning4j.nn.graph.vertex.GraphVertex
-
Whether the GraphVertex can do backward pass.
- canDoBackward() - Method in class org.deeplearning4j.nn.graph.vertex.impl.LayerVertex
-
- canDoForward() - Method in class org.deeplearning4j.nn.graph.vertex.BaseGraphVertex
-
- canDoForward() - Method in class org.deeplearning4j.nn.graph.vertex.BaseWrapperVertex
-
- canDoForward() - Method in interface org.deeplearning4j.nn.graph.vertex.GraphVertex
-
Whether the GraphVertex can do forward pass.
- capacity - Variable in class org.deeplearning4j.parallelism.MagicQueue
-
Deprecated.
- categoryMap - Variable in class com.atilika.kuromoji.compile.UnknownDictionaryCompiler
-
- CBOW<T extends SequenceElement> - Class in org.deeplearning4j.models.embeddings.learning.impl.elements
-
CBOW implementation for DeepLearning4j
- CBOW() - Constructor for class org.deeplearning4j.models.embeddings.learning.impl.elements.CBOW
-
- cbow(int, List<T>, int, AtomicLong, double, int) - Method in class org.deeplearning4j.models.embeddings.learning.impl.elements.CBOW
-
- Cell - Class in org.deeplearning4j.clustering.quadtree
-
A cell representing a bounding box forthe quad tree
- Cell(double, double, double, double) - Constructor for class org.deeplearning4j.clustering.quadtree.Cell
-
- Cell - Class in org.deeplearning4j.clustering.sptree
-
- Cell(int) - Constructor for class org.deeplearning4j.clustering.sptree.Cell
-
- CENTER_KEY - Static variable in class org.deeplearning4j.nn.params.CenterLossParamInitializer
-
- CenterLossOutputLayer - Class in org.deeplearning4j.nn.conf.layers
-
Center loss is similar to triplet loss except that it enforces
intraclass consistency and doesn't require feed forward of multiple
examples.
- CenterLossOutputLayer(CenterLossOutputLayer.Builder) - Constructor for class org.deeplearning4j.nn.conf.layers.CenterLossOutputLayer
-
- CenterLossOutputLayer - Class in org.deeplearning4j.nn.layers.training
-
Center loss is similar to triplet loss except that it enforces
intraclass consistency and doesn't require feed forward of multiple
examples.
- CenterLossOutputLayer(NeuralNetConfiguration) - Constructor for class org.deeplearning4j.nn.layers.training.CenterLossOutputLayer
-
- CenterLossOutputLayer(NeuralNetConfiguration, INDArray) - Constructor for class org.deeplearning4j.nn.layers.training.CenterLossOutputLayer
-
- CenterLossOutputLayer.Builder - Class in org.deeplearning4j.nn.conf.layers
-
- CenterLossParamInitializer - Class in org.deeplearning4j.nn.params
-
Initialize Center Loss params.
- CenterLossParamInitializer() - Constructor for class org.deeplearning4j.nn.params.CenterLossParamInitializer
-
- CGVaeReconstructionErrorWithKeyFunction<K> - Class in org.deeplearning4j.spark.impl.graph.scoring
-
Function to calculate the reconstruction error for a variational autoencoder, that is the first layer in a
ComputationGraph.
Note that the VAE must be using a loss function, not a
ReconstructionDistribution
Also note that scoring is batched for computational efficiency.
- CGVaeReconstructionErrorWithKeyFunction(Broadcast<INDArray>, Broadcast<String>, int) - Constructor for class org.deeplearning4j.spark.impl.graph.scoring.CGVaeReconstructionErrorWithKeyFunction
-
- CGVaeReconstructionProbWithKeyFunction<K> - Class in org.deeplearning4j.spark.impl.graph.scoring
-
Function to calculate the reconstruction probability for a variational autoencoder, that is the first layer in a
ComputationGraph.
Note that scoring is batched for computational efficiency.
- CGVaeReconstructionProbWithKeyFunction(Broadcast<INDArray>, Broadcast<String>, boolean, int, int) - Constructor for class org.deeplearning4j.spark.impl.graph.scoring.CGVaeReconstructionProbWithKeyFunction
-
- CHANNELS - Static variable in class org.deeplearning4j.datasets.iterator.impl.CifarDataSetIterator
-
- CHARACTER_DEFINITIONS_FILENAME - Static variable in class com.atilika.kuromoji.dict.CharacterDefinitions
-
- CharacterDefinitions - Class in com.atilika.kuromoji.dict
-
- CharacterDefinitions(int[][], int[][], String[]) - Constructor for class com.atilika.kuromoji.dict.CharacterDefinitions
-
- characterDefinitions - Variable in class com.atilika.kuromoji.TokenizerBase.Builder
-
- CharacterDefinitionsCompiler - Class in com.atilika.kuromoji.compile
-
- CharacterDefinitionsCompiler(OutputStream) - Constructor for class com.atilika.kuromoji.compile.CharacterDefinitionsCompiler
-
- chars - Variable in class org.ansj.splitWord.impl.GetWordsImpl
-
- chars - Variable in class org.ansj.util.Graph
-
- Chart - Class in org.deeplearning4j.ui.components.chart
-
Abstract class for charts
- Chart(String) - Constructor for class org.deeplearning4j.ui.components.chart.Chart
-
- Chart(String, Chart.Builder) - Constructor for class org.deeplearning4j.ui.components.chart.Chart
-
- Chart.Builder<T extends Chart.Builder<T>> - Class in org.deeplearning4j.ui.components.chart
-
- CHART_MAX_POINTS_PROPERTY - Static variable in class org.deeplearning4j.ui.module.train.TrainModule
-
- ChartHistogram - Class in org.deeplearning4j.ui.components.chart
-
Histogram chart, with pre-binned values.
- ChartHistogram(ChartHistogram.Builder) - Constructor for class org.deeplearning4j.ui.components.chart.ChartHistogram
-
- ChartHistogram() - Constructor for class org.deeplearning4j.ui.components.chart.ChartHistogram
-
- ChartHistogram.Builder - Class in org.deeplearning4j.ui.components.chart
-
- ChartHorizontalBar - Class in org.deeplearning4j.ui.components.chart
-
- ChartHorizontalBar() - Constructor for class org.deeplearning4j.ui.components.chart.ChartHorizontalBar
-
- ChartHorizontalBar.Builder - Class in org.deeplearning4j.ui.components.chart
-
- ChartLine - Class in org.deeplearning4j.ui.components.chart
-
Line chart with multiple independent series
- ChartLine() - Constructor for class org.deeplearning4j.ui.components.chart.ChartLine
-
- ChartLine.Builder - Class in org.deeplearning4j.ui.components.chart
-
- ChartScatter - Class in org.deeplearning4j.ui.components.chart
-
Scatter chart
- ChartScatter() - Constructor for class org.deeplearning4j.ui.components.chart.ChartScatter
-
- ChartScatter.Builder - Class in org.deeplearning4j.ui.components.chart
-
- ChartStackedArea - Class in org.deeplearning4j.ui.components.chart
-
Stacked area chart (no normalization), with multiple series.
- ChartStackedArea() - Constructor for class org.deeplearning4j.ui.components.chart.ChartStackedArea
-
- ChartStackedArea(ChartStackedArea.Builder) - Constructor for class org.deeplearning4j.ui.components.chart.ChartStackedArea
-
- ChartStackedArea.Builder - Class in org.deeplearning4j.ui.components.chart
-
- ChartTimeline - Class in org.deeplearning4j.ui.components.chart
-
A timeline/swimlane chart with zoom/scroll functionality.
- ChartTimeline() - Constructor for class org.deeplearning4j.ui.components.chart.ChartTimeline
-
- ChartTimeline.Builder - Class in org.deeplearning4j.ui.components.chart
-
- ChartTimeline.TimelineEntry - Class in org.deeplearning4j.ui.components.chart
-
- checkCuda(int) - Static method in class org.deeplearning4j.nn.layers.BaseCudnnHelper
-
- checkCudnn(int) - Static method in class org.deeplearning4j.nn.layers.BaseCudnnHelper
-
- checkForUnsupportedConfigurations(Map<String, Object>, boolean, KerasLayerConfiguration) - Static method in class org.deeplearning4j.nn.modelimport.keras.utils.KerasLayerUtils
-
Checks whether layer config contains unsupported options.
- checkGradients(MultiLayerNetwork, double, double, double, boolean, boolean, INDArray, INDArray) - Static method in class org.deeplearning4j.gradientcheck.GradientCheckUtil
-
Check backprop gradients for a MultiLayerNetwork.
- checkGradients(MultiLayerNetwork, double, double, double, boolean, boolean, INDArray, INDArray, INDArray, INDArray) - Static method in class org.deeplearning4j.gradientcheck.GradientCheckUtil
-
- checkGradients(MultiLayerNetwork, double, double, double, boolean, boolean, INDArray, INDArray, INDArray, INDArray, boolean, int) - Static method in class org.deeplearning4j.gradientcheck.GradientCheckUtil
-
- checkGradients(MultiLayerNetwork, double, double, double, boolean, boolean, INDArray, INDArray, INDArray, INDArray, boolean, int, Set<String>) - Static method in class org.deeplearning4j.gradientcheck.GradientCheckUtil
-
- checkGradients(ComputationGraph, double, double, double, boolean, boolean, INDArray[], INDArray[]) - Static method in class org.deeplearning4j.gradientcheck.GradientCheckUtil
-
Check backprop gradients for a ComputationGraph
- checkGradients(ComputationGraph, double, double, double, boolean, boolean, INDArray[], INDArray[], INDArray[], INDArray[]) - Static method in class org.deeplearning4j.gradientcheck.GradientCheckUtil
-
- checkGradients(ComputationGraph, double, double, double, boolean, boolean, INDArray[], INDArray[], INDArray[], INDArray[], Set<String>) - Static method in class org.deeplearning4j.gradientcheck.GradientCheckUtil
-
- checkGradientsPretrainLayer(Layer, double, double, double, boolean, boolean, INDArray, int) - Static method in class org.deeplearning4j.gradientcheck.GradientCheckUtil
-
Check backprop gradients for a pretrain layer
NOTE: gradient checking pretrain layers can be difficult...
- checkKryoConfiguration(JavaSparkContext, Logger) - Static method in class org.deeplearning4j.spark.util.SparkUtils
-
Check the spark configuration for incorrect Kryo configuration, logging a warning message if necessary
- checkModel(String) - Method in class org.ansj.app.crf.Model
-
判断当前数据流是否是本实例
- checkModel(String) - Method in class org.ansj.app.crf.model.CRFModel
-
- checkModel(String) - Method in class org.ansj.app.crf.model.CRFppTxtModel
-
- checkModel(String) - Method in class org.ansj.app.crf.model.WapitiCRFModel
-
- checkOutputException() - Method in class org.deeplearning4j.parallelism.inference.observers.BasicInferenceObservable
-
- Checkpoint - Class in org.deeplearning4j.optimize.listeners.checkpoint
-
- Checkpoint() - Constructor for class org.deeplearning4j.optimize.listeners.checkpoint.Checkpoint
-
- CheckpointListener - Class in org.deeplearning4j.optimize.listeners.checkpoint
-
CheckpointListener: The goal of this listener is to periodically save a copy of the model during training..
Model saving may be done:
1.
- CheckpointListener.Builder - Class in org.deeplearning4j.optimize.listeners.checkpoint
-
- checkStorageEvents(Persistable) - Method in class org.deeplearning4j.ui.storage.BaseCollectionStatsStorage
-
- checkStorageEvents(Persistable) - Method in class org.deeplearning4j.ui.storage.sqlite.J7FileStatsStorage
-
- CHECKSUM_TEST_FEATURES - Static variable in class org.deeplearning4j.datasets.fetchers.MnistDataFetcher
-
- CHECKSUM_TEST_LABELS - Static variable in class org.deeplearning4j.datasets.fetchers.MnistDataFetcher
-
- CHECKSUM_TRAIN_FEATURES - Static variable in class org.deeplearning4j.datasets.fetchers.MnistDataFetcher
-
- CHECKSUM_TRAIN_LABELS - Static variable in class org.deeplearning4j.datasets.fetchers.MnistDataFetcher
-
- CHECKSUMS_TEST - Static variable in class org.deeplearning4j.datasets.fetchers.MnistDataFetcher
-
- CHECKSUMS_TRAIN - Static variable in class org.deeplearning4j.datasets.fetchers.MnistDataFetcher
-
- checkSupported() - Method in class org.deeplearning4j.nn.layers.BaseCudnnHelper
-
- checkSupported() - Method in interface org.deeplearning4j.nn.layers.convolution.ConvolutionHelper
-
- checkSupported() - Method in interface org.deeplearning4j.nn.layers.convolution.subsampling.SubsamplingHelper
-
- checkSupported(double) - Method in interface org.deeplearning4j.nn.layers.normalization.BatchNormalizationHelper
-
- checkSupported(double) - Method in class org.deeplearning4j.nn.layers.normalization.CudnnBatchNormalizationHelper
-
- checkSupported(double, double, double, double) - Method in class org.deeplearning4j.nn.layers.normalization.CudnnLocalResponseNormalizationHelper
-
- checkSupported(double, double, double, double) - Method in interface org.deeplearning4j.nn.layers.normalization.LocalResponseNormalizationHelper
-
- checkSupported(IActivation, IActivation, boolean) - Method in class org.deeplearning4j.nn.layers.recurrent.CudnnLSTMHelper
-
- checkSupported(IActivation, IActivation, boolean) - Method in interface org.deeplearning4j.nn.layers.recurrent.LSTMHelper
-
- checkTerminalConditions(INDArray, double, double, int) - Method in interface org.deeplearning4j.optimize.api.ConvexOptimizer
-
Check termination conditions
setup a search state
- checkTerminalConditions(INDArray, double, double, int) - Method in class org.deeplearning4j.optimize.solvers.BaseOptimizer
-
- checkTree() - Method in class org.deeplearning4j.models.embeddings.reader.impl.TreeModelUtils
-
- children() - Method in class org.deeplearning4j.nn.layers.feedforward.autoencoder.recursive.Tree
-
- ChineseTokenizer - Class in org.deeplearning4j.text.tokenization.tokenizer
-
The ansj_seg of the open source segmentation algorithm comes form github,the link: https://github.com/NLPchina/ansj_seg
When the open source code that obeyed the Apache 2.0 license is reused, its latest commit ID is dedc45fdf85dfd2d4c691fb1f147d7cbf9a5d7fb
and its copyright 2011-2016
- ChineseTokenizer() - Constructor for class org.deeplearning4j.text.tokenization.tokenizer.ChineseTokenizer
-
- ChineseTokenizer(String) - Constructor for class org.deeplearning4j.text.tokenization.tokenizer.ChineseTokenizer
-
- ChineseTokenizerFactory - Class in org.deeplearning4j.text.tokenization.tokenizerFactory
-
- ChineseTokenizerFactory() - Constructor for class org.deeplearning4j.text.tokenization.tokenizerFactory.ChineseTokenizerFactory
-
- choleskyFromMatrix(RealMatrix) - Method in class org.deeplearning4j.clustering.util.MathUtils
-
This will return the cholesky decomposition of
the given matrix
- CifarDataSetIterator - Class in org.deeplearning4j.datasets.iterator.impl
-
CifarDataSetIterator is an iterator for Cifar10 dataset explicitly
There is a special preProcessor used to normalize the dataset based on Sergey Zagoruyko example
https://github.com/szagoruyko/cifar.torch
- CifarDataSetIterator(int, int) - Constructor for class org.deeplearning4j.datasets.iterator.impl.CifarDataSetIterator
-
Loads images with given batchSize & numExamples returned by the generator.
- CifarDataSetIterator(int, int, boolean) - Constructor for class org.deeplearning4j.datasets.iterator.impl.CifarDataSetIterator
-
Loads images with given batchSize, numExamples, & version returned by the generator.
- CifarDataSetIterator(int, int[]) - Constructor for class org.deeplearning4j.datasets.iterator.impl.CifarDataSetIterator
-
Loads images with given batchSize & imgDim returned by the generator.
- CifarDataSetIterator(int, int, int[]) - Constructor for class org.deeplearning4j.datasets.iterator.impl.CifarDataSetIterator
-
Loads images with given batchSize, numExamples, & imgDim returned by the generator.
- CifarDataSetIterator(int, int, int[], boolean) - Constructor for class org.deeplearning4j.datasets.iterator.impl.CifarDataSetIterator
-
Loads images with given batchSize, numExamples, imgDim & version returned by the generator.
- CifarDataSetIterator(int, int, int[], boolean, boolean) - Constructor for class org.deeplearning4j.datasets.iterator.impl.CifarDataSetIterator
-
Loads images with given batchSize, numExamples, imgDim & version returned by the generator.
- CifarDataSetIterator(int, int, int[], int, ImageTransform, boolean, boolean) - Constructor for class org.deeplearning4j.datasets.iterator.impl.CifarDataSetIterator
-
Create Cifar data specific iterator
- CifarDataSetIterator(int, int, int[], int, ImageTransform, boolean, boolean, long, boolean) - Constructor for class org.deeplearning4j.datasets.iterator.impl.CifarDataSetIterator
-
Create Cifar data specific iterator
- clamp(int, int, int) - Static method in class org.deeplearning4j.clustering.util.MathUtils
-
Clamps the value to a discrete value
- classCount(Integer) - Method in class org.deeplearning4j.eval.Evaluation
-
Returns the number of times the given label
has actually occurred
- classForScore(Double) - Method in class org.deeplearning4j.text.corpora.sentiwordnet.SWN3
-
- classification - Variable in class org.deeplearning4j.aws.emr.EmrConfig
-
- classification(int, int) - Method in class org.deeplearning4j.datasets.datavec.RecordReaderDataSetIterator.Builder
-
Use this for classification
- ClassificationScoreCalculator - Class in org.deeplearning4j.earlystopping.scorecalc
-
Score function for evaluating a MultiLayerNetwork according to an evaluation metric (Evaluation.Metric such
as accuracy, F1 score, etc.
- ClassificationScoreCalculator(Evaluation.Metric, DataSetIterator) - Constructor for class org.deeplearning4j.earlystopping.scorecalc.ClassificationScoreCalculator
-
- Classifier - Interface in org.deeplearning4j.nn.api
-
A classifier (this is for supervised learning)
- classify(String) - Method in class org.deeplearning4j.text.corpora.sentiwordnet.SWN3
-
Classifies the given text
- classify(CAS) - Method in class org.deeplearning4j.text.corpora.sentiwordnet.SWN3
-
- classify(Sentence) - Method in class org.deeplearning4j.text.corpora.sentiwordnet.SWN3
-
- classifyPoint(Point) - Method in class org.deeplearning4j.clustering.cluster.ClusterSet
-
- classifyPoint(Point, boolean) - Method in class org.deeplearning4j.clustering.cluster.ClusterSet
-
- classifyPoint(ClusterSet, Point) - Static method in class org.deeplearning4j.clustering.cluster.ClusterUtils
-
- classifyPoints() - Method in class org.deeplearning4j.clustering.algorithm.BaseClusteringAlgorithm
-
- classifyPoints(List<Point>) - Method in class org.deeplearning4j.clustering.cluster.ClusterSet
-
- classifyPoints(List<Point>, boolean) - Method in class org.deeplearning4j.clustering.cluster.ClusterSet
-
- classifyPoints(ClusterSet, List<Point>, ExecutorService) - Static method in class org.deeplearning4j.clustering.cluster.ClusterUtils
-
Classify the set of points base on cluster centers.
- className - Variable in class org.deeplearning4j.nn.modelimport.keras.KerasLayer
-
- className - Variable in class org.deeplearning4j.nn.modelimport.keras.KerasModel
-
- ClassPrediction - Class in org.deeplearning4j.zoo.util
-
ClassPrediction: a prediction for classification, used with a
Labels class.
- ClassPrediction() - Constructor for class org.deeplearning4j.zoo.util.ClassPrediction
-
- cleanup - Variable in class org.deeplearning4j.bagofwords.vectorizer.Builder
-
Deprecated.
- cleanup(boolean) - Method in class org.deeplearning4j.bagofwords.vectorizer.Builder
-
Deprecated.
- cleanup() - Method in interface org.deeplearning4j.text.invertedindex.InvertedIndex
-
Cleanup any resources used
- clear() - Method in class com.atilika.kuromoji.trie.PatriciaTrie
-
Clears this trie by removing all its key-value pairs
- clear(String) - Static method in class org.ansj.library.DicLibrary
-
将用户自定义词典清空
- clear() - Method in class org.ansj.recognition.impl.StopRecognition
-
- clear() - Method in interface org.deeplearning4j.nn.api.Model
-
Clear input
- clear() - Method in class org.deeplearning4j.nn.conf.layers.samediff.SDLayerParams
-
Clear any previously set weight/bias parameters (including their shapes)
- clear() - Method in class org.deeplearning4j.nn.gradient.DefaultGradient
-
- clear() - Method in interface org.deeplearning4j.nn.gradient.Gradient
-
Clear residual parameters (useful for returning a gradient and then clearing old objects)
- clear() - Method in class org.deeplearning4j.nn.graph.ComputationGraph
-
- clear() - Method in class org.deeplearning4j.nn.graph.vertex.BaseGraphVertex
-
- clear() - Method in class org.deeplearning4j.nn.graph.vertex.BaseWrapperVertex
-
- clear() - Method in interface org.deeplearning4j.nn.graph.vertex.GraphVertex
-
Clear the internal state (if any) of the GraphVertex.
- clear() - Method in class org.deeplearning4j.nn.layers.AbstractLayer
-
- clear() - Method in class org.deeplearning4j.nn.layers.BaseLayer
-
- clear() - Method in class org.deeplearning4j.nn.layers.BaseOutputLayer
-
- clear() - Method in class org.deeplearning4j.nn.layers.LossLayer
-
- clear() - Method in class org.deeplearning4j.nn.layers.recurrent.BidirectionalLayer
-
- clear() - Method in class org.deeplearning4j.nn.layers.variational.VariationalAutoencoder
-
- clear() - Method in class org.deeplearning4j.nn.layers.wrapper.BaseWrapperLayer
-
- clear() - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
-
Clear the inputs.
- clear() - Method in class org.deeplearning4j.optimize.solvers.accumulation.FancyBlockingQueue
-
- clear() - Method in class org.deeplearning4j.parallelism.ConcurrentHashSet
-
Deprecated.
- clear() - Method in class org.deeplearning4j.parallelism.MagicQueue
-
Deprecated.
- clear() - Method in class org.deeplearning4j.plot.BarnesHutTsne
-
- clear() - Method in class org.deeplearning4j.ui.stats.sbe.InitFieldsPresentEncoder
-
- clear() - Method in class org.deeplearning4j.ui.stats.sbe.UpdateFieldsPresentEncoder
-
- clear() - Method in class org.deeplearning4j.util.DiskBasedQueue
-
- clearLayerMaskArrays() - Method in class org.deeplearning4j.nn.graph.ComputationGraph
-
- clearLayerMaskArrays() - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
-
- clearLayersStates() - Method in class org.deeplearning4j.nn.graph.ComputationGraph
-
This method just makes sure there's no state preserved within layers
- clearLayersStates() - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
-
This method just makes sure there's no state preserved within layers
- clearNoiseWeightParams() - Method in interface org.deeplearning4j.nn.api.Layer
-
- clearNoiseWeightParams() - Method in class org.deeplearning4j.nn.layers.ActivationLayer
-
- clearNoiseWeightParams() - Method in class org.deeplearning4j.nn.layers.BaseLayer
-
- clearNoiseWeightParams() - Method in class org.deeplearning4j.nn.layers.convolution.Cropping1DLayer
-
- clearNoiseWeightParams() - Method in class org.deeplearning4j.nn.layers.convolution.Cropping2DLayer
-
- clearNoiseWeightParams() - Method in class org.deeplearning4j.nn.layers.convolution.Cropping3DLayer
-
- clearNoiseWeightParams() - Method in class org.deeplearning4j.nn.layers.convolution.SpaceToBatch
-
- clearNoiseWeightParams() - Method in class org.deeplearning4j.nn.layers.convolution.SpaceToDepth
-
- clearNoiseWeightParams() - Method in class org.deeplearning4j.nn.layers.convolution.subsampling.Subsampling3DLayer
-
- clearNoiseWeightParams() - Method in class org.deeplearning4j.nn.layers.convolution.subsampling.SubsamplingLayer
-
- clearNoiseWeightParams() - Method in class org.deeplearning4j.nn.layers.convolution.upsampling.Upsampling2D
-
- clearNoiseWeightParams() - Method in class org.deeplearning4j.nn.layers.convolution.upsampling.Upsampling3D
-
- clearNoiseWeightParams() - Method in class org.deeplearning4j.nn.layers.convolution.ZeroPadding1DLayer
-
- clearNoiseWeightParams() - Method in class org.deeplearning4j.nn.layers.convolution.ZeroPadding3DLayer
-
- clearNoiseWeightParams() - Method in class org.deeplearning4j.nn.layers.convolution.ZeroPaddingLayer
-
- clearNoiseWeightParams() - Method in class org.deeplearning4j.nn.layers.normalization.LocalResponseNormalization
-
- clearNoiseWeightParams() - Method in class org.deeplearning4j.nn.layers.objdetect.Yolo2OutputLayer
-
- clearNoiseWeightParams() - Method in class org.deeplearning4j.nn.layers.pooling.GlobalPoolingLayer
-
- clearNoiseWeightParams() - Method in class org.deeplearning4j.nn.layers.recurrent.BidirectionalLayer
-
- clearNoiseWeightParams() - Method in class org.deeplearning4j.nn.layers.samediff.SameDiffLayer
-
- clearNoiseWeightParams() - Method in class org.deeplearning4j.nn.layers.util.MaskLayer
-
- clearNoiseWeightParams() - Method in class org.deeplearning4j.nn.layers.variational.VariationalAutoencoder
-
- clearNoiseWeightParams() - Method in class org.deeplearning4j.nn.layers.wrapper.BaseWrapperLayer
-
- clearNoiseWeightParams() - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
-
- clearScore() - Method in class org.ansj.domain.Term
-
将term的所有分数置为0
- clearTbpttState - Variable in class org.deeplearning4j.nn.graph.ComputationGraph
-
- clearTbpttState - Variable in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
-
- clearVariables() - Method in class org.deeplearning4j.nn.conf.NeuralNetConfiguration
-
- clearVertex() - Method in class org.deeplearning4j.nn.graph.vertex.BaseGraphVertex
-
- clearVertex() - Method in class org.deeplearning4j.nn.graph.vertex.BaseWrapperVertex
-
- clearVertex() - Method in interface org.deeplearning4j.nn.graph.vertex.GraphVertex
-
This method clears inpjut for this vertex
- clipboard - Variable in class org.deeplearning4j.spark.parameterserver.networking.SilentTrainingDriver
-
- clone() - Method in interface org.deeplearning4j.api.storage.listener.RoutingIterationListener
-
- clone() - Method in class org.deeplearning4j.eval.ROC.CountsForThreshold
-
- clone() - Method in interface org.deeplearning4j.nn.api.Layer
-
Deprecated.
- clone() - Method in interface org.deeplearning4j.nn.api.layers.LayerConstraint
-
- clone() - Method in class org.deeplearning4j.nn.conf.ComputationGraphConfiguration
-
- clone() - Method in class org.deeplearning4j.nn.conf.constraint.BaseConstraint
-
- clone() - Method in class org.deeplearning4j.nn.conf.constraint.MaxNormConstraint
-
- clone() - Method in class org.deeplearning4j.nn.conf.constraint.MinMaxNormConstraint
-
- clone() - Method in class org.deeplearning4j.nn.conf.constraint.NonNegativeConstraint
-
- clone() - Method in class org.deeplearning4j.nn.conf.constraint.UnitNormConstraint
-
- clone() - Method in class org.deeplearning4j.nn.conf.distribution.Distribution
-
- clone() - Method in class org.deeplearning4j.nn.conf.dropout.AlphaDropout
-
- clone() - Method in class org.deeplearning4j.nn.conf.dropout.Dropout
-
- clone() - Method in class org.deeplearning4j.nn.conf.dropout.GaussianDropout
-
- clone() - Method in class org.deeplearning4j.nn.conf.dropout.GaussianNoise
-
- clone() - Method in interface org.deeplearning4j.nn.conf.dropout.IDropout
-
- clone() - Method in class org.deeplearning4j.nn.conf.dropout.SpatialDropout
-
- clone() - Method in class org.deeplearning4j.nn.conf.graph.ElementWiseVertex
-
- clone() - Method in class org.deeplearning4j.nn.conf.graph.FrozenVertex
-
- clone() - Method in class org.deeplearning4j.nn.conf.graph.GraphVertex
-
- clone() - Method in class org.deeplearning4j.nn.conf.graph.L2NormalizeVertex
-
- clone() - Method in class org.deeplearning4j.nn.conf.graph.L2Vertex
-
- clone() - Method in class org.deeplearning4j.nn.conf.graph.LayerVertex
-
- clone() - Method in class org.deeplearning4j.nn.conf.graph.MergeVertex
-
- clone() - Method in class org.deeplearning4j.nn.conf.graph.PoolHelperVertex
-
- clone() - Method in class org.deeplearning4j.nn.conf.graph.PreprocessorVertex
-
- clone() - Method in class org.deeplearning4j.nn.conf.graph.ReshapeVertex
-
- clone() - Method in class org.deeplearning4j.nn.conf.graph.rnn.DuplicateToTimeSeriesVertex
-
- clone() - Method in class org.deeplearning4j.nn.conf.graph.rnn.LastTimeStepVertex
-
- clone() - Method in class org.deeplearning4j.nn.conf.graph.rnn.ReverseTimeSeriesVertex
-
- clone() - Method in class org.deeplearning4j.nn.conf.graph.ScaleVertex
-
- clone() - Method in class org.deeplearning4j.nn.conf.graph.ShiftVertex
-
- clone() - Method in class org.deeplearning4j.nn.conf.graph.StackVertex
-
- clone() - Method in class org.deeplearning4j.nn.conf.graph.SubsetVertex
-
- clone() - Method in class org.deeplearning4j.nn.conf.graph.UnstackVertex
-
- clone() - Method in interface org.deeplearning4j.nn.conf.InputPreProcessor
-
- clone() - Method in class org.deeplearning4j.nn.conf.layers.ActivationLayer
-
- clone() - Method in class org.deeplearning4j.nn.conf.layers.BaseLayer
-
- clone() - Method in class org.deeplearning4j.nn.conf.layers.BaseUpsamplingLayer
-
- clone() - Method in class org.deeplearning4j.nn.conf.layers.BatchNormalization
-
- clone() - Method in class org.deeplearning4j.nn.conf.layers.Convolution3D
-
- clone() - Method in class org.deeplearning4j.nn.conf.layers.ConvolutionLayer
-
- clone() - Method in class org.deeplearning4j.nn.conf.layers.Deconvolution2D
-
- clone() - Method in class org.deeplearning4j.nn.conf.layers.DepthwiseConvolution2D
-
- clone() - Method in class org.deeplearning4j.nn.conf.layers.DropoutLayer
-
- clone() - Method in class org.deeplearning4j.nn.conf.layers.Layer
-
- clone() - Method in class org.deeplearning4j.nn.conf.layers.LocalResponseNormalization
-
- clone() - Method in class org.deeplearning4j.nn.conf.layers.misc.ElementWiseMultiplicationLayer
-
- clone() - Method in class org.deeplearning4j.nn.conf.layers.misc.FrozenLayer
-
- clone() - Method in class org.deeplearning4j.nn.conf.layers.misc.FrozenLayerWithBackprop
-
- clone() - Method in class org.deeplearning4j.nn.conf.layers.SeparableConvolution2D
-
- clone() - Method in class org.deeplearning4j.nn.conf.layers.SpaceToBatchLayer
-
- clone() - Method in class org.deeplearning4j.nn.conf.layers.SpaceToDepthLayer
-
- clone() - Method in class org.deeplearning4j.nn.conf.layers.Subsampling1DLayer
-
- clone() - Method in class org.deeplearning4j.nn.conf.layers.Subsampling3DLayer
-
- clone() - Method in class org.deeplearning4j.nn.conf.layers.SubsamplingLayer
-
- clone() - Method in class org.deeplearning4j.nn.conf.layers.Upsampling1D
-
- clone() - Method in class org.deeplearning4j.nn.conf.layers.Upsampling2D
-
- clone() - Method in class org.deeplearning4j.nn.conf.layers.Upsampling3D
-
- clone() - Method in class org.deeplearning4j.nn.conf.MultiLayerConfiguration
-
- clone() - Method in class org.deeplearning4j.nn.conf.NeuralNetConfiguration.Builder
-
- clone() - Method in class org.deeplearning4j.nn.conf.NeuralNetConfiguration
-
Creates and returns a deep copy of the configuration.
- clone() - Method in class org.deeplearning4j.nn.conf.preprocessor.BaseInputPreProcessor
-
- clone() - Method in class org.deeplearning4j.nn.conf.preprocessor.Cnn3DToFeedForwardPreProcessor
-
- clone() - Method in class org.deeplearning4j.nn.conf.preprocessor.CnnToFeedForwardPreProcessor
-
- clone() - Method in class org.deeplearning4j.nn.conf.preprocessor.CnnToRnnPreProcessor
-
- clone() - Method in class org.deeplearning4j.nn.conf.preprocessor.ComposableInputPreProcessor
-
- clone() - Method in class org.deeplearning4j.nn.conf.preprocessor.FeedForwardToCnn3DPreProcessor
-
- clone() - Method in class org.deeplearning4j.nn.conf.preprocessor.FeedForwardToCnnPreProcessor
-
- clone() - Method in class org.deeplearning4j.nn.conf.preprocessor.FeedForwardToRnnPreProcessor
-
- clone() - Method in class org.deeplearning4j.nn.conf.preprocessor.RnnToCnnPreProcessor
-
- clone() - Method in class org.deeplearning4j.nn.conf.preprocessor.RnnToFeedForwardPreProcessor
-
- clone() - Method in class org.deeplearning4j.nn.conf.preprocessor.UnitVarianceProcessor
-
- clone() - Method in class org.deeplearning4j.nn.conf.stepfunctions.StepFunction
-
- clone() - Method in class org.deeplearning4j.nn.conf.weightnoise.DropConnect
-
- clone() - Method in interface org.deeplearning4j.nn.conf.weightnoise.IWeightNoise
-
- clone() - Method in class org.deeplearning4j.nn.conf.weightnoise.WeightNoise
-
- clone() - Method in class org.deeplearning4j.nn.graph.ComputationGraph
-
- clone() - Method in class org.deeplearning4j.nn.layers.AbstractLayer
-
- clone() - Method in class org.deeplearning4j.nn.layers.ActivationLayer
-
- clone() - Method in class org.deeplearning4j.nn.layers.BaseLayer
-
- clone() - Method in class org.deeplearning4j.nn.layers.convolution.Cropping1DLayer
-
- clone() - Method in class org.deeplearning4j.nn.layers.convolution.Cropping2DLayer
-
- clone() - Method in class org.deeplearning4j.nn.layers.convolution.Cropping3DLayer
-
- clone() - Method in class org.deeplearning4j.nn.layers.convolution.SpaceToBatch
-
- clone() - Method in class org.deeplearning4j.nn.layers.convolution.SpaceToDepth
-
- clone() - Method in class org.deeplearning4j.nn.layers.convolution.subsampling.Subsampling3DLayer
-
- clone() - Method in class org.deeplearning4j.nn.layers.convolution.subsampling.SubsamplingLayer
-
- clone() - Method in class org.deeplearning4j.nn.layers.convolution.upsampling.Upsampling2D
-
- clone() - Method in class org.deeplearning4j.nn.layers.convolution.upsampling.Upsampling3D
-
- clone() - Method in class org.deeplearning4j.nn.layers.convolution.ZeroPadding1DLayer
-
- clone() - Method in class org.deeplearning4j.nn.layers.convolution.ZeroPadding3DLayer
-
- clone() - Method in class org.deeplearning4j.nn.layers.convolution.ZeroPaddingLayer
-
- clone() - Method in class org.deeplearning4j.nn.layers.feedforward.autoencoder.recursive.Tree
-
- clone() - Method in class org.deeplearning4j.nn.layers.FrozenLayer
-
- clone() - Method in class org.deeplearning4j.nn.layers.FrozenLayerWithBackprop
-
- clone() - Method in class org.deeplearning4j.nn.layers.normalization.BatchNormalization
-
- clone() - Method in class org.deeplearning4j.nn.layers.normalization.LocalResponseNormalization
-
- clone() - Method in class org.deeplearning4j.nn.layers.objdetect.Yolo2OutputLayer
-
- clone() - Method in class org.deeplearning4j.nn.layers.pooling.GlobalPoolingLayer
-
- clone() - Method in class org.deeplearning4j.nn.layers.recurrent.BidirectionalLayer
-
- clone() - Method in class org.deeplearning4j.nn.layers.samediff.SameDiffLayer
-
- clone() - Method in class org.deeplearning4j.nn.layers.util.MaskLayer
-
- clone() - Method in class org.deeplearning4j.nn.layers.variational.VariationalAutoencoder
-
- clone() - Method in class org.deeplearning4j.nn.layers.wrapper.BaseWrapperLayer
-
- clone() - Method in class org.deeplearning4j.nn.modelimport.keras.preprocessors.KerasFlattenRnnPreprocessor
-
- clone() - Method in class org.deeplearning4j.nn.modelimport.keras.preprocessors.TensorFlowCnnToFeedForwardPreProcessor
-
- clone() - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
-
Clones the multilayernetwork
- clone() - Method in class org.deeplearning4j.nn.updater.MultiLayerUpdater
-
- clone() - Method in class org.deeplearning4j.ui.stats.BaseStatsListener
-
- clone() - Method in class org.deeplearning4j.ui.stats.J7StatsListener
-
- clone() - Method in class org.deeplearning4j.ui.stats.StatsListener
-
- cloneListener(TrainingListener) - Static method in class org.deeplearning4j.parallelism.trainer.DefaultTrainer
-
- close() - Method in class org.ansj.util.AnsjReader
-
- close() - Method in interface org.deeplearning4j.api.storage.StatsStorage
-
Close any open resources (files, etc)
- close() - Method in class org.deeplearning4j.datasets.mnist.MnistManager
-
Close any resources opened by the manager.
- close() - Method in class org.deeplearning4j.models.embeddings.loader.WordVectorSerializer.BinaryReader
-
- close() - Method in class org.deeplearning4j.models.embeddings.loader.WordVectorSerializer.CSVReader
-
- close() - Method in class org.deeplearning4j.nn.modelimport.keras.Hdf5Archive
-
- close() - Method in class org.deeplearning4j.nn.modelimport.keras.utils.KerasModelBuilder
-
- close() - Method in class org.deeplearning4j.parallelism.ParallelWrapper
-
- close() - Method in class org.deeplearning4j.spark.datavec.iterator.SparkSourceDummyReader
-
- close() - Method in class org.deeplearning4j.ui.storage.InMemoryStatsStorage
-
- close() - Method in class org.deeplearning4j.ui.storage.mapdb.MapDBStatsStorage
-
- close() - Method in class org.deeplearning4j.ui.storage.sqlite.J7FileStatsStorage
-
- Cluster - Class in org.deeplearning4j.clustering.cluster
-
A cluster.
- Cluster() - Constructor for class org.deeplearning4j.clustering.cluster.Cluster
-
- Cluster(Point, String) - Constructor for class org.deeplearning4j.clustering.cluster.Cluster
-
- Cluster(Point, boolean, String) - Constructor for class org.deeplearning4j.clustering.cluster.Cluster
-
- ClusterInfo - Class in org.deeplearning4j.clustering.info
-
- ClusterInfo(boolean) - Constructor for class org.deeplearning4j.clustering.info.ClusterInfo
-
- ClusterInfo(boolean, boolean) - Constructor for class org.deeplearning4j.clustering.info.ClusterInfo
-
- ClusteringAlgorithm - Interface in org.deeplearning4j.clustering.algorithm
-
An interface for a clustering
algorithm.
- ClusteringAlgorithmCondition - Interface in org.deeplearning4j.clustering.condition
-
- ClusteringOptimization - Class in org.deeplearning4j.clustering.optimisation
-
- ClusteringOptimization() - Constructor for class org.deeplearning4j.clustering.optimisation.ClusteringOptimization
-
- ClusteringOptimizationType - Enum in org.deeplearning4j.clustering.optimisation
-
- ClusteringStrategy - Interface in org.deeplearning4j.clustering.strategy
-
- ClusteringStrategyType - Enum in org.deeplearning4j.clustering.strategy
-
- clusterName(String) - Method in class org.deeplearning4j.aws.emr.SparkEMRClient.Builder
-
Defines the EMR cluster's name
- ClusterSet - Class in org.deeplearning4j.clustering.cluster
-
- ClusterSet(boolean) - Constructor for class org.deeplearning4j.clustering.cluster.ClusterSet
-
- ClusterSet(String, boolean) - Constructor for class org.deeplearning4j.clustering.cluster.ClusterSet
-
- ClusterSetInfo - Class in org.deeplearning4j.clustering.info
-
- ClusterSetInfo(boolean) - Constructor for class org.deeplearning4j.clustering.info.ClusterSetInfo
-
- ClusterSetInfo(boolean, boolean) - Constructor for class org.deeplearning4j.clustering.info.ClusterSetInfo
-
- ClusterSetup - Class in org.deeplearning4j.aws.ec2.provision
-
Sets up a DL4J cluster
- ClusterSetup(String[]) - Constructor for class org.deeplearning4j.aws.ec2.provision.ClusterSetup
-
- ClusterUtils - Class in org.deeplearning4j.clustering.cluster
-
Basic cluster utilities
- ClusterUtils() - Constructor for class org.deeplearning4j.clustering.cluster.ClusterUtils
-
- Cnn3DToFeedForwardPreProcessor - Class in org.deeplearning4j.nn.conf.preprocessor
-
A preprocessor to allow CNN and standard feed-forward network layers to be used together.
For example, CNN3D -> Denselayer
This does two things:
(b) Reshapes 5d activations out of CNN layer, with shape
[numExamples, numChannels, inputDepth, inputHeight, inputWidth]) into 2d activations (with shape
[numExamples, inputDepth*inputHeight*inputWidth*numChannels]) for use in feed forward layer
(a) Reshapes epsilons (weights*deltas) out of FeedFoward layer (which is 2D or 3D with shape
[numExamples, inputDepth* inputHeight*inputWidth*numChannels]) into 5d epsilons (with shape
[numExamples, numChannels, inputDepth, inputHeight, inputWidth]) suitable to feed into CNN layers.
Note: numChannels is equivalent to featureMaps referenced in different literature
- Cnn3DToFeedForwardPreProcessor(int, int, int, int, boolean) - Constructor for class org.deeplearning4j.nn.conf.preprocessor.Cnn3DToFeedForwardPreProcessor
-
- Cnn3DToFeedForwardPreProcessor(int, int, int) - Constructor for class org.deeplearning4j.nn.conf.preprocessor.Cnn3DToFeedForwardPreProcessor
-
- Cnn3DToFeedForwardPreProcessor() - Constructor for class org.deeplearning4j.nn.conf.preprocessor.Cnn3DToFeedForwardPreProcessor
-
- CnnLossLayer - Class in org.deeplearning4j.nn.conf.layers
-
Convolutional Neural Network Loss Layer.
Handles calculation of gradients etc for various objective functions.
NOTE: CnnLossLayer does not have any parameters.
- CnnLossLayer - Class in org.deeplearning4j.nn.layers.convolution
-
Convolutional Neural Network Loss Layer.
Handles calculation of gradients etc for various objective functions.
NOTE: CnnLossLayer does not have any parameters.
- CnnLossLayer(NeuralNetConfiguration) - Constructor for class org.deeplearning4j.nn.layers.convolution.CnnLossLayer
-
- CnnLossLayer.Builder - Class in org.deeplearning4j.nn.conf.layers
-
- CnnSentenceDataSetIterator - Class in org.deeplearning4j.iterator
-
A DataSetIterator that provides data for training a CNN sentence classification models (though can of course
be used for general documents, not just sentences.
- CnnSentenceDataSetIterator.Builder - Class in org.deeplearning4j.iterator
-
- CnnSentenceDataSetIterator.UnknownWordHandling - Enum in org.deeplearning4j.iterator
-
- CnnToFeedForwardPreProcessor - Class in org.deeplearning4j.nn.conf.preprocessor
-
A preprocessor to allow CNN and standard feed-forward network layers to be used together.
For example, CNN -> Denselayer
This does two things:
(b) Reshapes 4d activations out of CNN layer, with shape
[numExamples, numChannels, inputHeight, inputWidth]) into 2d activations (with shape
[numExamples, inputHeight*inputWidth*numChannels]) for use in feed forward layer
(a) Reshapes epsilons (weights*deltas) out of FeedFoward layer (which is 2D or 3D with shape
[numExamples, inputHeight*inputWidth*numChannels]) into 4d epsilons (with shape
[numExamples, numChannels, inputHeight, inputWidth]) suitable to feed into CNN layers.
Note: numChannels is equivalent to channels or featureMaps referenced in different literature
- CnnToFeedForwardPreProcessor(int, int, int) - Constructor for class org.deeplearning4j.nn.conf.preprocessor.CnnToFeedForwardPreProcessor
-
- CnnToFeedForwardPreProcessor(int, int) - Constructor for class org.deeplearning4j.nn.conf.preprocessor.CnnToFeedForwardPreProcessor
-
- CnnToFeedForwardPreProcessor() - Constructor for class org.deeplearning4j.nn.conf.preprocessor.CnnToFeedForwardPreProcessor
-
- CnnToRnnPreProcessor - Class in org.deeplearning4j.nn.conf.preprocessor
-
A preprocessor to allow CNN and RNN layers to be used together.
For example, ConvolutionLayer -> GravesLSTM
Functionally equivalent to combining CnnToFeedForwardPreProcessor + FeedForwardToRnnPreProcessor
Specifically, this does two things:
(a) Reshape 4d activations out of CNN layer, with shape [timeSeriesLength*miniBatchSize, numChannels, inputHeight, inputWidth])
into 3d (time series) activations (with shape [numExamples, inputHeight*inputWidth*numChannels, timeSeriesLength])
for use in RNN layers
(b) Reshapes 3d epsilons (weights.*deltas) out of RNN layer (with shape
[miniBatchSize,inputHeight*inputWidth*numChannels,timeSeriesLength]) into 4d epsilons with shape
[miniBatchSize*timeSeriesLength, numChannels, inputHeight, inputWidth] suitable to feed into CNN layers.
- CnnToRnnPreProcessor(int, int, int) - Constructor for class org.deeplearning4j.nn.conf.preprocessor.CnnToRnnPreProcessor
-
- cntGet - Variable in class org.deeplearning4j.parallelism.MagicQueue
-
Deprecated.
- cntPut - Variable in class org.deeplearning4j.parallelism.MagicQueue
-
Deprecated.
- COALESCE_THRESHOLD - Static variable in class org.deeplearning4j.spark.impl.paramavg.ParameterAveragingTrainingMaster
-
- COCOLabels - Class in org.deeplearning4j.zoo.util.darknet
-
Helper class that returns label descriptions for YOLO models trained with
COCO.
- COCOLabels() - Constructor for class org.deeplearning4j.zoo.util.darknet.COCOLabels
-
- codec - Variable in class org.deeplearning4j.spark.models.sequencevectors.export.impl.HdfsModelExporter
-
- codeLength - Variable in class org.deeplearning4j.models.sequencevectors.sequence.SequenceElement
-
- codes - Variable in class org.deeplearning4j.models.embeddings.inmemory.InMemoryLookupTable
-
- codes - Variable in class org.deeplearning4j.models.sequencevectors.sequence.SequenceElement
-
- COEFFICIENTS_BIN - Static variable in class org.deeplearning4j.util.ModelSerializer
-
- cohesion(String) - Method in class org.ansj.app.crf.SplitWord
-
随便给一个词。计算这个词的内聚分值，可以理解为计算这个词的可信度
- collapseDimensions(boolean) - Method in class org.deeplearning4j.nn.conf.layers.GlobalPoolingLayer.Builder
-
Whether to collapse dimensions when pooling or not.
- CollapseUnaries - Class in org.deeplearning4j.text.corpora.treeparser
-
Collapse unaries such that the
tree is only made of preterminals and leaves.
- CollapseUnaries() - Constructor for class org.deeplearning4j.text.corpora.treeparser.CollapseUnaries
-
- collectGarbageCollectionStats() - Method in interface org.deeplearning4j.ui.stats.api.StatsUpdateConfiguration
-
Should garbage collection stats be collected and reported?
- collectGarbageCollectionStats(boolean) - Method in class org.deeplearning4j.ui.stats.impl.DefaultStatsUpdateConfiguration.Builder
-
- collectGarbageCollectionStats() - Method in class org.deeplearning4j.ui.stats.impl.DefaultStatsUpdateConfiguration
-
- collectHardwareInfo() - Method in interface org.deeplearning4j.ui.stats.api.StatsInitializationConfiguration
-
Should hardware configuration information be collected? JVM available processors, number of devices, total memory for each device
- collectHardwareInfo() - Method in class org.deeplearning4j.ui.stats.impl.DefaultStatsInitializationConfiguration
-
- collectHistograms(StatsType) - Method in interface org.deeplearning4j.ui.stats.api.StatsUpdateConfiguration
-
Should histograms (per parameter type, or per layer for activations) of the given type be collected?
- collectHistograms(StatsType) - Method in class org.deeplearning4j.ui.stats.impl.DefaultStatsUpdateConfiguration
-
- collectHistogramsActivations(boolean) - Method in class org.deeplearning4j.ui.stats.impl.DefaultStatsUpdateConfiguration.Builder
-
- collectHistogramsGradients(boolean) - Method in class org.deeplearning4j.ui.stats.impl.DefaultStatsUpdateConfiguration.Builder
-
- collectHistogramsParameters(boolean) - Method in class org.deeplearning4j.ui.stats.impl.DefaultStatsUpdateConfiguration.Builder
-
- collectHistogramsUpdates(boolean) - Method in class org.deeplearning4j.ui.stats.impl.DefaultStatsUpdateConfiguration.Builder
-
- CollectionLabeledSentenceProvider - Class in org.deeplearning4j.iterator.provider
-
Iterate over a set of sentences/documents,
where the sentences and labels are provided in lists.
- CollectionLabeledSentenceProvider(List<String>, List<String>) - Constructor for class org.deeplearning4j.iterator.provider.CollectionLabeledSentenceProvider
-
- CollectionLabeledSentenceProvider(List<String>, List<String>, Random) - Constructor for class org.deeplearning4j.iterator.provider.CollectionLabeledSentenceProvider
-
- CollectionSentenceIterator - Class in org.deeplearning4j.text.sentenceiterator
-
- CollectionSentenceIterator(SentencePreProcessor, Collection<String>) - Constructor for class org.deeplearning4j.text.sentenceiterator.CollectionSentenceIterator
-
- CollectionSentenceIterator(Collection<String>) - Constructor for class org.deeplearning4j.text.sentenceiterator.CollectionSentenceIterator
-
- CollectionStatsStorageRouter - Class in org.deeplearning4j.api.storage.impl
-
A simple StatsStorageRouter that simply stores the metadata, static info and updates in the specified
collections.
- CollectionStatsStorageRouter() - Constructor for class org.deeplearning4j.api.storage.impl.CollectionStatsStorageRouter
-
- collectLearningRates() - Method in interface org.deeplearning4j.ui.stats.api.StatsUpdateConfiguration
-
Should per-parameter type learning rates be collected and reported?
- collectLearningRates(boolean) - Method in class org.deeplearning4j.ui.stats.impl.DefaultStatsUpdateConfiguration.Builder
-
- collectLearningRates() - Method in class org.deeplearning4j.ui.stats.impl.DefaultStatsUpdateConfiguration
-
- collectMean(StatsType) - Method in interface org.deeplearning4j.ui.stats.api.StatsUpdateConfiguration
-
Should the mean values (per parameter type, or per layer for activations) be collected?
- collectMean(StatsType) - Method in class org.deeplearning4j.ui.stats.impl.DefaultStatsUpdateConfiguration
-
- collectMeanActivations(boolean) - Method in class org.deeplearning4j.ui.stats.impl.DefaultStatsUpdateConfiguration.Builder
-
- collectMeanGradients(boolean) - Method in class org.deeplearning4j.ui.stats.impl.DefaultStatsUpdateConfiguration.Builder
-
- collectMeanMagnitudes(StatsType) - Method in interface org.deeplearning4j.ui.stats.api.StatsUpdateConfiguration
-
Should the mean magnitude values (per parameter type, or per layer for activations) be collected?
- collectMeanMagnitudes(StatsType) - Method in class org.deeplearning4j.ui.stats.impl.DefaultStatsUpdateConfiguration
-
- collectMeanMagnitudesActivations(boolean) - Method in class org.deeplearning4j.ui.stats.impl.DefaultStatsUpdateConfiguration.Builder
-
- collectMeanMagnitudesGradients(boolean) - Method in class org.deeplearning4j.ui.stats.impl.DefaultStatsUpdateConfiguration.Builder
-
- collectMeanMagnitudesParameters(boolean) - Method in class org.deeplearning4j.ui.stats.impl.DefaultStatsUpdateConfiguration.Builder
-
- collectMeanMagnitudesUpdates(boolean) - Method in class org.deeplearning4j.ui.stats.impl.DefaultStatsUpdateConfiguration.Builder
-
- collectMeanParameters(boolean) - Method in class org.deeplearning4j.ui.stats.impl.DefaultStatsUpdateConfiguration.Builder
-
- collectMeanUpdates(boolean) - Method in class org.deeplearning4j.ui.stats.impl.DefaultStatsUpdateConfiguration.Builder
-
- collectMemoryStats() - Method in interface org.deeplearning4j.ui.stats.api.StatsUpdateConfiguration
-
Should JVM, off-heap and memory stats be collected/reported?
- collectMemoryStats(boolean) - Method in class org.deeplearning4j.ui.stats.impl.DefaultStatsUpdateConfiguration.Builder
-
- collectMemoryStats() - Method in class org.deeplearning4j.ui.stats.impl.DefaultStatsUpdateConfiguration
-
- collectMetaData(boolean) - Method in class org.deeplearning4j.datasets.datavec.RecordReaderDataSetIterator.Builder
-
When set to true: metadata for the current examples will be present in the returned DataSet.
- collectModelInfo() - Method in interface org.deeplearning4j.ui.stats.api.StatsInitializationConfiguration
-
Should model information be collected? Model class, configuration (JSON), number of layers, number of parameters, etc.
- collectModelInfo() - Method in class org.deeplearning4j.ui.stats.impl.DefaultStatsInitializationConfiguration
-
- collectPerformanceStats() - Method in interface org.deeplearning4j.ui.stats.api.StatsUpdateConfiguration
-
Should performance stats be collected/reported?
Total time, total examples, total batches, Minibatches/second, examples/second
- collectPerformanceStats(boolean) - Method in class org.deeplearning4j.ui.stats.impl.DefaultStatsUpdateConfiguration.Builder
-
- collectPerformanceStats() - Method in class org.deeplearning4j.ui.stats.impl.DefaultStatsUpdateConfiguration
-
- CollectScoresIterationListener - Class in org.deeplearning4j.optimize.listeners
-
CollectScoresIterationListener simply stores the model scores internally (along with the iteration) every 1 or N
iterations (this is configurable).
- CollectScoresIterationListener() - Constructor for class org.deeplearning4j.optimize.listeners.CollectScoresIterationListener
-
Constructor for collecting scores with default saving frequency of 1
- CollectScoresIterationListener(int) - Constructor for class org.deeplearning4j.optimize.listeners.CollectScoresIterationListener
-
Constructor for collecting scores with the specified frequency.
- CollectScoresListener - Class in org.deeplearning4j.optimize.listeners
-
A simple listener that collects scores to a list every N iterations.
- CollectScoresListener(int) - Constructor for class org.deeplearning4j.optimize.listeners.CollectScoresListener
-
- CollectScoresListener(int, boolean) - Constructor for class org.deeplearning4j.optimize.listeners.CollectScoresListener
-
- collectSoftwareInfo() - Method in interface org.deeplearning4j.ui.stats.api.StatsInitializationConfiguration
-
Should software configuration information be collected? For example, OS, JVM, and ND4J backend details
- collectSoftwareInfo() - Method in class org.deeplearning4j.ui.stats.impl.DefaultStatsInitializationConfiguration
-
- collectStdev(StatsType) - Method in interface org.deeplearning4j.ui.stats.api.StatsUpdateConfiguration
-
Should the standard devication values (per parameter type, or per layer for activations) be collected?
- collectStdev(StatsType) - Method in class org.deeplearning4j.ui.stats.impl.DefaultStatsUpdateConfiguration
-
- collectStdevActivations(boolean) - Method in class org.deeplearning4j.ui.stats.impl.DefaultStatsUpdateConfiguration.Builder
-
- collectStdevGradients(boolean) - Method in class org.deeplearning4j.ui.stats.impl.DefaultStatsUpdateConfiguration.Builder
-
- collectStdevParameters(boolean) - Method in class org.deeplearning4j.ui.stats.impl.DefaultStatsUpdateConfiguration.Builder
-
- collectStdevUpdates(boolean) - Method in class org.deeplearning4j.ui.stats.impl.DefaultStatsUpdateConfiguration.Builder
-
- collectTrainingStats - Variable in class org.deeplearning4j.spark.api.WorkerConfiguration
-
- collectTrainingStats - Variable in class org.deeplearning4j.spark.impl.paramavg.BaseTrainingMaster
-
- collectTrainingStats - Variable in class org.deeplearning4j.spark.parameterserver.training.SharedTrainingMaster.Builder
-
- collectTrainingStats(boolean) - Method in class org.deeplearning4j.spark.parameterserver.training.SharedTrainingMaster.Builder
-
Enable/disable collection of training statistics
- collectTrainingStats - Variable in class org.deeplearning4j.spark.parameterserver.training.SharedTrainingMaster
-
- color(Color) - Method in class org.deeplearning4j.ui.components.text.style.StyleText.Builder
-
Color for the text
- color(String) - Method in class org.deeplearning4j.ui.components.text.style.StyleText.Builder
-
Color for the text
- colorToHex(Color) - Static method in class org.deeplearning4j.ui.api.Utils
-
Convert an AWT color to a hex color string, such as #000000
- columnWidths(LengthUnit, double...) - Method in class org.deeplearning4j.ui.components.table.style.StyleTable.Builder
-
Specify the widths for the columns
- com.atilika.kuromoji - package com.atilika.kuromoji
-
- com.atilika.kuromoji.buffer - package com.atilika.kuromoji.buffer
-
- com.atilika.kuromoji.compile - package com.atilika.kuromoji.compile
-
- com.atilika.kuromoji.dict - package com.atilika.kuromoji.dict
-
- com.atilika.kuromoji.io - package com.atilika.kuromoji.io
-
- com.atilika.kuromoji.ipadic - package com.atilika.kuromoji.ipadic
-
- com.atilika.kuromoji.ipadic.compile - package com.atilika.kuromoji.ipadic.compile
-
- com.atilika.kuromoji.trie - package com.atilika.kuromoji.trie
-
- com.atilika.kuromoji.util - package com.atilika.kuromoji.util
-
- com.atilika.kuromoji.viterbi - package com.atilika.kuromoji.viterbi
-
- combination(double, double) - Static method in class org.deeplearning4j.clustering.util.MathUtils
-
This returns the combination of n choose r
- CombinedMultiDataSetPreProcessor - Class in org.deeplearning4j.datasets.iterator
-
Combines various multidataset preprocessors
Applied in the order they are specified to in the builder
- CombinedMultiDataSetPreProcessor.Builder - Class in org.deeplearning4j.datasets.iterator
-
- CombinedPreProcessor - Class in org.deeplearning4j.datasets.iterator
-
This is special preProcessor, that allows to combine multiple prerpocessors, and apply them to data sequentially.
- CombinedPreProcessor.Builder - Class in org.deeplearning4j.datasets.iterator
-
- combinedSequentialFileInputStream(File) - Method in class com.atilika.kuromoji.compile.TokenInfoDictionaryCompilerBase
-
- CommonPreprocessor - Class in org.deeplearning4j.text.tokenization.tokenizer.preprocessor
-
A ToeknPreProcess implementation that removes puncuation marks and lower-cases.
- CommonPreprocessor() - Constructor for class org.deeplearning4j.text.tokenization.tokenizer.preprocessor.CommonPreprocessor
-
- CommonSparkTrainingStats - Class in org.deeplearning4j.spark.api.stats
-
- CommonSparkTrainingStats() - Constructor for class org.deeplearning4j.spark.api.stats.CommonSparkTrainingStats
-
- CommonSparkTrainingStats.Builder - Class in org.deeplearning4j.spark.api.stats
-
- CommunicativeTrainer - Interface in org.deeplearning4j.parallelism.trainer
-
- CompactModelAndGradient - Class in org.deeplearning4j.ui.weights.beans
-
Slightly modified version of ModelAndGradient, with binned params/gradients, suitable for fast network transfers for HistogramIterationListener
- CompactModelAndGradient() - Constructor for class org.deeplearning4j.ui.weights.beans.CompactModelAndGradient
-
- CompanyAttrLibrary - Class in org.ansj.library.company
-
机构名识别词典加载类
- compare(HeapObject, HeapObject) - Method in class org.deeplearning4j.clustering.vptree.VPTree.HeapObjectComparator
-
- compare(Double[], Double[]) - Method in class org.deeplearning4j.models.embeddings.reader.impl.BasicModelUtils.ArrayComparator
-
- compare(BasicModelUtils.WordSimilarity, BasicModelUtils.WordSimilarity) - Method in class org.deeplearning4j.models.embeddings.reader.impl.BasicModelUtils.SimilarityComparator
-
- compare(Vertex<V>, Vertex<V>) - Method in class org.deeplearning4j.models.sequencevectors.graph.walkers.impl.NearestVertexWalker.VertexComparator
-
- compare(PopularityWalker.Node<T>, PopularityWalker.Node<T>) - Method in class org.deeplearning4j.models.sequencevectors.graph.walkers.impl.PopularityWalker.NodeComparator
-
- compare(DataSet, DataSet) - Method in class org.deeplearning4j.spark.ordering.DataSetOrdering
-
- compare(EventStats, EventStats) - Method in class org.deeplearning4j.spark.stats.StatsUtils.StartTimeComparator
-
- compareTo(Keyword) - Method in class org.ansj.app.keyword.Keyword
-
- compareTo(HeapItem) - Method in class org.deeplearning4j.clustering.sptree.HeapItem
-
- compareTo(HeapObject) - Method in class org.deeplearning4j.clustering.sptree.HeapObject
-
- compareTo(SequenceElement) - Method in class org.deeplearning4j.models.sequencevectors.sequence.SequenceElement
-
- compareTo(BaseCollectionStatsStorage.SessionTypeId) - Method in class org.deeplearning4j.ui.storage.BaseCollectionStatsStorage.SessionTypeId
-
- compareTo(BaseCollectionStatsStorage.SessionTypeWorkerId) - Method in class org.deeplearning4j.ui.storage.BaseCollectionStatsStorage.SessionTypeWorkerId
-
- compile() - Method in class com.atilika.kuromoji.compile.CharacterDefinitionsCompiler
-
- compile() - Method in interface com.atilika.kuromoji.compile.Compiler
-
- compile() - Method in class com.atilika.kuromoji.compile.ConnectionCostsCompiler
-
- compile() - Method in class com.atilika.kuromoji.compile.TokenInfoBufferCompiler
-
- compile() - Method in class com.atilika.kuromoji.compile.TokenInfoDictionaryCompilerBase
-
- compile() - Method in class com.atilika.kuromoji.compile.UnknownDictionaryCompiler
-
- compile() - Method in class com.atilika.kuromoji.compile.WordIdMapCompiler
-
- Compiler - Interface in com.atilika.kuromoji.compile
-
- Component - Class in org.deeplearning4j.ui.api
-
A component is anything that can be rendered, such at charts, text or tables.
- Component(String, Style) - Constructor for class org.deeplearning4j.ui.api.Component
-
- COMPONENT_TYPE - Static variable in class org.deeplearning4j.ui.components.chart.ChartHistogram
-
- COMPONENT_TYPE - Static variable in class org.deeplearning4j.ui.components.chart.ChartHorizontalBar
-
- COMPONENT_TYPE - Static variable in class org.deeplearning4j.ui.components.chart.ChartLine
-
- COMPONENT_TYPE - Static variable in class org.deeplearning4j.ui.components.chart.ChartScatter
-
- COMPONENT_TYPE - Static variable in class org.deeplearning4j.ui.components.chart.ChartStackedArea
-
- COMPONENT_TYPE - Static variable in class org.deeplearning4j.ui.components.chart.ChartTimeline
-
- COMPONENT_TYPE - Static variable in class org.deeplearning4j.ui.components.component.ComponentDiv
-
- COMPONENT_TYPE - Static variable in class org.deeplearning4j.ui.components.decorator.DecoratorAccordion
-
- COMPONENT_TYPE - Static variable in class org.deeplearning4j.ui.components.table.ComponentTable
-
- COMPONENT_TYPE - Static variable in class org.deeplearning4j.ui.components.text.ComponentText
-
- ComponentDiv - Class in org.deeplearning4j.ui.components.component
-
Div component (as in, HTML div)
- ComponentDiv() - Constructor for class org.deeplearning4j.ui.components.component.ComponentDiv
-
- ComponentDiv(Style, Component...) - Constructor for class org.deeplearning4j.ui.components.component.ComponentDiv
-
- ComponentDiv(Style, Collection<Component>) - Constructor for class org.deeplearning4j.ui.components.component.ComponentDiv
-
- ComponentObject - Class in org.deeplearning4j.ui.standalone
-
Created by Alex on 25/03/2016.
- ComponentObject() - Constructor for class org.deeplearning4j.ui.standalone.ComponentObject
-
- ComponentTable - Class in org.deeplearning4j.ui.components.table
-
Simple 2d table for text,
- ComponentTable() - Constructor for class org.deeplearning4j.ui.components.table.ComponentTable
-
- ComponentTable(ComponentTable.Builder) - Constructor for class org.deeplearning4j.ui.components.table.ComponentTable
-
- ComponentTable(String[], String[][], StyleTable) - Constructor for class org.deeplearning4j.ui.components.table.ComponentTable
-
- ComponentTable.Builder - Class in org.deeplearning4j.ui.components.table
-
- ComponentText - Class in org.deeplearning4j.ui.components.text
-
Simple text component with styling
- ComponentText() - Constructor for class org.deeplearning4j.ui.components.text.ComponentText
-
- ComponentText(String, StyleText) - Constructor for class org.deeplearning4j.ui.components.text.ComponentText
-
- ComponentText.Builder - Class in org.deeplearning4j.ui.components.text
-
- componentType - Variable in class org.deeplearning4j.ui.api.Component
-
Component type: used by the Arbiter UI to determine how to decode and render the object which is
represented by the JSON representation of this object
- ComposableInputPreProcessor - Class in org.deeplearning4j.nn.conf.preprocessor
-
Composable input pre processor
- ComposableInputPreProcessor(InputPreProcessor...) - Constructor for class org.deeplearning4j.nn.conf.preprocessor.ComposableInputPreProcessor
-
- ComposableIterationListener - Class in org.deeplearning4j.optimize.listeners
-
A group of listeners
- ComposableIterationListener(TrainingListener...) - Constructor for class org.deeplearning4j.optimize.listeners.ComposableIterationListener
-
- ComposableIterationListener(Collection<TrainingListener>) - Constructor for class org.deeplearning4j.optimize.listeners.ComposableIterationListener
-
- CompositeReconstructionDistribution - Class in org.deeplearning4j.nn.conf.layers.variational
-
CompositeReconstructionDistribution is a reconstruction distribution built from multiple other ReconstructionDistribution
instances.
The typical use is to combine for example continuous and binary data in the same model, or to combine different
distributions for continuous variables.
- CompositeReconstructionDistribution(int[], ReconstructionDistribution[], int) - Constructor for class org.deeplearning4j.nn.conf.layers.variational.CompositeReconstructionDistribution
-
- CompositeReconstructionDistribution.Builder - Class in org.deeplearning4j.nn.conf.layers.variational
-
- compressor - Variable in class org.deeplearning4j.optimize.solvers.accumulation.EncodingHandler
-
- compuNatureFreq(NatureRecognition.NatureTerm, NatureRecognition.NatureTerm) - Static method in class org.ansj.util.MathUtil
-
两个词性之间的分数计算
- compuScore(Term, Term, Map<String, Double>) - Static method in class org.ansj.util.MathUtil
-
从一个词的词性到另一个词的词的分数
- compuScoreFreq(Term, Term) - Static method in class org.ansj.util.MathUtil
-
词性词频词长.计算出来一个分数
- ComputationGraph - Class in org.deeplearning4j.nn.graph
-
A ComputationGraph network is a neural network with arbitrary (directed acyclic graph) connection structure.
- ComputationGraph(ComputationGraphConfiguration) - Constructor for class org.deeplearning4j.nn.graph.ComputationGraph
-
- computationGraph - Variable in class org.deeplearning4j.streaming.routes.DL4jServeRouteBuilder
-
- ComputationGraphConfiguration - Class in org.deeplearning4j.nn.conf
-
ComputationGraphConfiguration is a configuration object for neural networks with arbitrary connection structure.
- ComputationGraphConfiguration() - Constructor for class org.deeplearning4j.nn.conf.ComputationGraphConfiguration
-
- ComputationGraphConfiguration.GraphBuilder - Class in org.deeplearning4j.nn.conf
-
- ComputationGraphConfigurationDeserializer - Class in org.deeplearning4j.nn.conf.serde
-
- ComputationGraphConfigurationDeserializer(JsonDeserializer<?>) - Constructor for class org.deeplearning4j.nn.conf.serde.ComputationGraphConfigurationDeserializer
-
- ComputationGraphUpdater - Class in org.deeplearning4j.nn.updater.graph
-
Gradient updater for ComputationGraph.
- ComputationGraphUpdater(ComputationGraph) - Constructor for class org.deeplearning4j.nn.updater.graph.ComputationGraphUpdater
-
- ComputationGraphUpdater(ComputationGraph, INDArray) - Constructor for class org.deeplearning4j.nn.updater.graph.ComputationGraphUpdater
-
- computationGraphUpdater - Variable in class org.deeplearning4j.optimize.solvers.BaseOptimizer
-
- ComputationGraphUtil - Class in org.deeplearning4j.nn.graph.util
-
- compute(PortableDataStream) - Method in class org.deeplearning4j.spark.parameterserver.callbacks.DataSetDeserializationCallback
-
- compute(PortableDataStream) - Method in class org.deeplearning4j.spark.parameterserver.callbacks.MultiDataSetDeserializationCallback
-
- compute(PortableDataStream) - Method in interface org.deeplearning4j.spark.parameterserver.callbacks.PortableDataStreamCallback
-
This method should do something, and return DataSet after all
- compute(PortableDataStream) - Method in interface org.deeplearning4j.spark.parameterserver.callbacks.PortableDataStreamMDSCallback
-
This method should do something, and return DataSet after all
- computeArticleTfidf(String, String) - Method in class org.ansj.app.keyword.KeyWordComputer
-
- computeArticleTfidf(String) - Method in class org.ansj.app.keyword.KeyWordComputer
-
只有正文
- computeClusterInfos(Cluster, String) - Static method in class org.deeplearning4j.clustering.cluster.ClusterUtils
-
- computeClusterSetInfo(ClusterSet) - Static method in class org.deeplearning4j.clustering.cluster.ClusterUtils
-
- computeClusterSetInfo(ClusterSet, ExecutorService) - Static method in class org.deeplearning4j.clustering.cluster.ClusterUtils
-
- computeDistance(String, INDArray, INDArray, INDArray) - Static method in class org.deeplearning4j.clustering.randomprojection.RPUtils
-
/**
Compute the distance between 2 vectors
given a function name.
- computeDistance(String, INDArray, INDArray) - Static method in class org.deeplearning4j.clustering.randomprojection.RPUtils
-
Compute the distance between 2 vectors
given a function name.
- computeDistanceMulti(String, INDArray, INDArray, INDArray) - Static method in class org.deeplearning4j.clustering.randomprojection.RPUtils
-
Compute the distance between 2 vectors
given a function name.
- computeEdgeForces(INDArray, INDArray, INDArray, int, INDArray) - Method in class org.deeplearning4j.clustering.quadtree.QuadTree
-
- computeEdgeForces(INDArray, INDArray, INDArray, int, INDArray) - Method in class org.deeplearning4j.clustering.sptree.SpTree
-
Compute edge forces using barnes hut
- computeGaussianKernel(INDArray, double, int) - Method in class org.deeplearning4j.plot.BarnesHutTsne
-
Computes a gaussian kernel
given a vector of squared distance distances
- computeGaussianPerplexity(INDArray, double) - Method in class org.deeplearning4j.plot.BarnesHutTsne
-
Convert data to probability
co-occurrences (aka calculating the kernel)
- computeGradient(INDArray, INDArray, IActivation, INDArray) - Method in class org.deeplearning4j.nn.layers.ocnn.OCNNOutputLayer.OCNNLossFunction
-
- computeGradientAndScore(LayerWorkspaceMgr) - Method in interface org.deeplearning4j.nn.api.Model
-
Update the score
- computeGradientAndScore(LayerWorkspaceMgr) - Method in class org.deeplearning4j.nn.graph.ComputationGraph
-
- computeGradientAndScore() - Method in class org.deeplearning4j.nn.graph.ComputationGraph
-
- computeGradientAndScore(LayerWorkspaceMgr) - Method in class org.deeplearning4j.nn.layers.AbstractLayer
-
- computeGradientAndScore(LayerWorkspaceMgr) - Method in class org.deeplearning4j.nn.layers.BaseLayer
-
- computeGradientAndScore(LayerWorkspaceMgr) - Method in class org.deeplearning4j.nn.layers.BaseOutputLayer
-
- computeGradientAndScore(LayerWorkspaceMgr) - Method in class org.deeplearning4j.nn.layers.feedforward.autoencoder.AutoEncoder
-
- computeGradientAndScore(LayerWorkspaceMgr) - Method in class org.deeplearning4j.nn.layers.FrozenLayer
-
- computeGradientAndScore(LayerWorkspaceMgr) - Method in class org.deeplearning4j.nn.layers.FrozenLayerWithBackprop
-
- computeGradientAndScore(LayerWorkspaceMgr) - Method in class org.deeplearning4j.nn.layers.LossLayer
-
- computeGradientAndScore(LayerWorkspaceMgr) - Method in class org.deeplearning4j.nn.layers.objdetect.Yolo2OutputLayer
-
- computeGradientAndScore(INDArray, INDArray, IActivation, INDArray, boolean) - Method in class org.deeplearning4j.nn.layers.ocnn.OCNNOutputLayer.OCNNLossFunction
-
- computeGradientAndScore(LayerWorkspaceMgr) - Method in class org.deeplearning4j.nn.layers.recurrent.BidirectionalLayer
-
- computeGradientAndScore(LayerWorkspaceMgr) - Method in class org.deeplearning4j.nn.layers.training.CenterLossOutputLayer
-
- computeGradientAndScore(LayerWorkspaceMgr) - Method in class org.deeplearning4j.nn.layers.variational.VariationalAutoencoder
-
- computeGradientAndScore(LayerWorkspaceMgr) - Method in class org.deeplearning4j.nn.layers.wrapper.BaseWrapperLayer
-
- computeGradientAndScore(LayerWorkspaceMgr) - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
-
- computeGradientAndScore() - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
-
- computeGradientAndScore(LayerWorkspaceMgr) - Method in class org.deeplearning4j.plot.BarnesHutTsne
-
- computeLossFunctionScoreArray(INDArray, INDArray) - Method in class org.deeplearning4j.nn.conf.layers.variational.CompositeReconstructionDistribution
-
- computeNonEdgeForces(int, double, INDArray, AtomicDouble) - Method in class org.deeplearning4j.clustering.quadtree.QuadTree
-
Compute non edge forces using barnes hut
- computeNonEdgeForces(int, double, INDArray, AtomicDouble) - Method in class org.deeplearning4j.clustering.sptree.SpTree
-
Compute non edge forces using barnes hut
- computeScore(double, double, boolean, LayerWorkspaceMgr) - Method in interface org.deeplearning4j.nn.api.layers.IOutputLayer
-
Compute score after labels and input have been set.
- computeScore(double, double, boolean, LayerWorkspaceMgr) - Method in class org.deeplearning4j.nn.graph.vertex.impl.LayerVertex
-
- computeScore(double, double, boolean, LayerWorkspaceMgr) - Method in class org.deeplearning4j.nn.layers.BaseOutputLayer
-
Compute score after labels and input have been set.
- computeScore(double, double, boolean, LayerWorkspaceMgr) - Method in class org.deeplearning4j.nn.layers.convolution.CnnLossLayer
-
- computeScore(double, double, boolean, LayerWorkspaceMgr) - Method in class org.deeplearning4j.nn.layers.LossLayer
-
Compute score after labels and input have been set.
- computeScore(double, double, boolean, LayerWorkspaceMgr) - Method in class org.deeplearning4j.nn.layers.objdetect.Yolo2OutputLayer
-
- computeScore(double, double, boolean, LayerWorkspaceMgr) - Method in class org.deeplearning4j.nn.layers.ocnn.OCNNOutputLayer
-
Compute score after labels and input have been set.
- computeScore(INDArray, INDArray, IActivation, INDArray, boolean) - Method in class org.deeplearning4j.nn.layers.ocnn.OCNNOutputLayer.OCNNLossFunction
-
- computeScore(double, double, boolean, LayerWorkspaceMgr) - Method in class org.deeplearning4j.nn.layers.recurrent.RnnLossLayer
-
- computeScore(double, double, boolean, LayerWorkspaceMgr) - Method in class org.deeplearning4j.nn.layers.training.CenterLossOutputLayer
-
Compute score after labels and input have been set.
- computeScore(VariationalAutoencoder, INDArray) - Method in class org.deeplearning4j.spark.impl.common.score.BaseVaeReconstructionProbWithKeyFunctionAdapter
-
- computeScore(VariationalAutoencoder, INDArray) - Method in class org.deeplearning4j.spark.impl.common.score.BaseVaeScoreWithKeyFunctionAdapter
-
- computeScore(VariationalAutoencoder, INDArray) - Method in class org.deeplearning4j.spark.impl.graph.scoring.CGVaeReconstructionErrorWithKeyFunction
-
- computeScoreArray(INDArray, INDArray, IActivation, INDArray) - Method in class org.deeplearning4j.nn.layers.ocnn.OCNNOutputLayer.OCNNLossFunction
-
- computeScoreForExamples(double, double, LayerWorkspaceMgr) - Method in interface org.deeplearning4j.nn.api.layers.IOutputLayer
-
Compute the score for each example individually, after labels and input have been set.
- computeScoreForExamples(double, double, LayerWorkspaceMgr) - Method in class org.deeplearning4j.nn.graph.vertex.impl.LayerVertex
-
- computeScoreForExamples(double, double, LayerWorkspaceMgr) - Method in class org.deeplearning4j.nn.layers.BaseOutputLayer
-
Compute the score for each example individually, after labels and input have been set.
- computeScoreForExamples(double, double, LayerWorkspaceMgr) - Method in class org.deeplearning4j.nn.layers.convolution.CnnLossLayer
-
Compute the score for each example individually, after labels and input have been set.
- computeScoreForExamples(double, double, LayerWorkspaceMgr) - Method in class org.deeplearning4j.nn.layers.LossLayer
-
Compute the score for each example individually, after labels and input have been set.
- computeScoreForExamples(double, double, LayerWorkspaceMgr) - Method in class org.deeplearning4j.nn.layers.objdetect.Yolo2OutputLayer
-
- computeScoreForExamples(double, double, LayerWorkspaceMgr) - Method in class org.deeplearning4j.nn.layers.ocnn.OCNNOutputLayer
-
Compute the score for each example individually, after labels and input have been set.
- computeScoreForExamples(double, double, LayerWorkspaceMgr) - Method in class org.deeplearning4j.nn.layers.recurrent.RnnLossLayer
-
Compute the score for each example individually, after labels and input have been set.
- computeScoreForExamples(double, double, LayerWorkspaceMgr) - Method in class org.deeplearning4j.nn.layers.recurrent.RnnOutputLayer
-
Compute the score for each example individually, after labels and input have been set.
- computeScoreForExamples(double, double, LayerWorkspaceMgr) - Method in class org.deeplearning4j.nn.layers.training.CenterLossOutputLayer
-
Compute the score for each example individually, after labels and input have been set.
- computeSquareDistancesFromNearestCluster(ClusterSet, List<Point>, INDArray, ExecutorService) - Static method in class org.deeplearning4j.clustering.cluster.ClusterUtils
-
- ConcurrentHashSet<E> - Class in org.deeplearning4j.parallelism
-
- ConcurrentHashSet() - Constructor for class org.deeplearning4j.parallelism.ConcurrentHashSet
-
Deprecated.
- ConcurrentHashSet(Collection<E>) - Constructor for class org.deeplearning4j.parallelism.ConcurrentHashSet
-
Deprecated.
- ConcurrentTokenizer - Class in org.deeplearning4j.text.tokenization.tokenizer
-
OpenNLP Tokenizer annotator.
- ConcurrentTokenizer() - Constructor for class org.deeplearning4j.text.tokenization.tokenizer.ConcurrentTokenizer
-
Initializes a new instance.
- conf() - Method in interface org.deeplearning4j.nn.api.Model
-
The configuration for the neural network
- conf() - Method in class org.deeplearning4j.nn.graph.ComputationGraph
-
- conf - Variable in class org.deeplearning4j.nn.layers.AbstractLayer
-
- conf() - Method in class org.deeplearning4j.nn.layers.AbstractLayer
-
- conf() - Method in class org.deeplearning4j.nn.layers.recurrent.BidirectionalLayer
-
- conf - Variable in class org.deeplearning4j.nn.layers.variational.VariationalAutoencoder
-
- conf() - Method in class org.deeplearning4j.nn.layers.variational.VariationalAutoencoder
-
- conf() - Method in class org.deeplearning4j.nn.layers.wrapper.BaseWrapperLayer
-
- conf - Variable in class org.deeplearning4j.nn.modelimport.keras.KerasLayer
-
- conf() - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
-
- conf - Variable in class org.deeplearning4j.optimize.solvers.BaseOptimizer
-
- conf() - Method in class org.deeplearning4j.plot.BarnesHutTsne
-
- conf() - Method in class org.deeplearning4j.zoo.model.AlexNet
-
- conf() - Method in class org.deeplearning4j.zoo.model.Darknet19
-
- conf() - Method in class org.deeplearning4j.zoo.model.FaceNetNN4Small2
-
- conf() - Method in class org.deeplearning4j.zoo.model.LeNet
-
- conf() - Method in class org.deeplearning4j.zoo.model.SimpleCNN
-
- conf() - Method in class org.deeplearning4j.zoo.model.TextGenerationLSTM
-
- conf() - Method in class org.deeplearning4j.zoo.model.TinyYOLO
-
- conf() - Method in class org.deeplearning4j.zoo.model.VGG16
-
- conf() - Method in class org.deeplearning4j.zoo.model.VGG19
-
- conf() - Method in class org.deeplearning4j.zoo.model.YOLO2
-
- Config - Class in org.ansj.app.crf
-
- Config(int[][]) - Constructor for class org.ansj.app.crf.Config
-
- config - Variable in class org.ansj.app.crf.Model
-
- config - Static variable in class org.deeplearning4j.nn.modelimport.keras.KerasModel
-
- config - Variable in class org.deeplearning4j.nn.modelimport.keras.utils.KerasModelBuilder
-
- configs - Variable in class org.deeplearning4j.aws.emr.EmrConfig
-
- configuration - Variable in class org.deeplearning4j.models.embeddings.learning.impl.elements.SkipGram
-
- configuration - Variable in class org.deeplearning4j.models.embeddings.learning.impl.sequence.DBOW
-
- configuration - Variable in class org.deeplearning4j.models.sequencevectors.SequenceVectors.Builder
-
- configuration - Variable in class org.deeplearning4j.models.sequencevectors.SequenceVectors
-
- configuration - Variable in class org.deeplearning4j.nn.graph.ComputationGraph
-
- configuration - Variable in class org.deeplearning4j.spark.models.embeddings.word2vec.Word2Vec.Builder
-
- configuration - Variable in class org.deeplearning4j.spark.models.embeddings.word2vec.Word2Vec
-
- configuration - Variable in class org.deeplearning4j.spark.models.sequencevectors.SparkSequenceVectors.Builder
-
- CONFIGURATION_JSON - Static variable in class org.deeplearning4j.util.ModelSerializer
-
- configurationBroadcast - Variable in class org.deeplearning4j.spark.models.sequencevectors.functions.BaseTokenizerFunction
-
- configurationBroadcast - Variable in class org.deeplearning4j.spark.models.sequencevectors.functions.DistributedFunction
-
- configurationBroadcast - Variable in class org.deeplearning4j.spark.models.sequencevectors.functions.PartitionTrainingFunction
-
- configurationBroadcast - Variable in class org.deeplearning4j.spark.models.sequencevectors.functions.TrainingFunction
-
- configurationBroadcast - Variable in class org.deeplearning4j.spark.models.sequencevectors.SparkSequenceVectors
-
- configure(TokenizerBase.Builder) - Method in class com.atilika.kuromoji.TokenizerBase
-
- configure(VocabCache<T>, WeightLookupTable<T>, VectorsConfiguration) - Method in interface org.deeplearning4j.models.embeddings.learning.ElementsLearningAlgorithm
-
- configure(VocabCache<T>, WeightLookupTable<T>, VectorsConfiguration) - Method in class org.deeplearning4j.models.embeddings.learning.impl.elements.CBOW
-
- configure(VocabCache<T>, WeightLookupTable<T>, VectorsConfiguration) - Method in class org.deeplearning4j.models.embeddings.learning.impl.elements.GloVe
-
- configure(VocabCache<T>, WeightLookupTable<T>, VectorsConfiguration) - Method in class org.deeplearning4j.models.embeddings.learning.impl.elements.SkipGram
-
SkipGram initialization over given vocabulary and WeightLookupTable
- configure(VocabCache<T>, WeightLookupTable<T>, VectorsConfiguration) - Method in class org.deeplearning4j.models.embeddings.learning.impl.sequence.DBOW
-
- configure(VocabCache<T>, WeightLookupTable<T>, VectorsConfiguration) - Method in class org.deeplearning4j.models.embeddings.learning.impl.sequence.DM
-
- configure(VocabCache<T>, WeightLookupTable<T>, VectorsConfiguration) - Method in interface org.deeplearning4j.models.embeddings.learning.SequenceLearningAlgorithm
-
- configure(NeuralNetConfiguration) - Method in class org.deeplearning4j.optimize.Solver.Builder
-
- configure(VocabCache<ShallowSequenceElement>, WeightLookupTable<ShallowSequenceElement>, VectorsConfiguration) - Method in class org.deeplearning4j.spark.models.sequencevectors.learning.elements.BaseSparkLearningAlgorithm
-
- configure(VocabCache<ShallowSequenceElement>, WeightLookupTable<ShallowSequenceElement>, VectorsConfiguration) - Method in class org.deeplearning4j.spark.models.sequencevectors.learning.sequence.BaseSparkSequenceLearningAlgorithm
-
- configure() - Method in class org.deeplearning4j.streaming.kafka.NDArrayPubSubRoute
-
Called on initialization to build the routes using the fluent builder syntax.
This is a central method for RouteBuilder implementations to implement
the routes using the Java fluent builder syntax.
- configure() - Method in class org.deeplearning4j.streaming.routes.CamelKafkaRouteBuilder
-
Let's configure the Camel routing rules using Java code...
- configure() - Method in class org.deeplearning4j.streaming.routes.DL4jServeRouteBuilder
-
Called on initialization to build the routes using the fluent builder syntax.
This is a central method for RouteBuilder implementations to implement
the routes using the Java fluent builder syntax.
- configured - Variable in class org.deeplearning4j.models.sequencevectors.SequenceVectors
-
- configureListeners(String, Collection<TrainingListener>, Collection<TrainingListener>) - Method in class org.deeplearning4j.parallelism.trainer.DefaultTrainer
-
- confs - Variable in class org.deeplearning4j.nn.conf.MultiLayerConfiguration.Builder
-
- confs(List<NeuralNetConfiguration>) - Method in class org.deeplearning4j.nn.conf.MultiLayerConfiguration.Builder
-
- confs - Variable in class org.deeplearning4j.nn.conf.MultiLayerConfiguration
-
- Confusion() - Constructor for class org.deeplearning4j.eval.curves.PrecisionRecallCurve.Confusion
-
- confusion - Variable in class org.deeplearning4j.eval.Evaluation
-
- CONFUSION_PRINT_MAX_CLASSES - Static variable in class org.deeplearning4j.eval.Evaluation
-
- ConfusionMatrix<T extends Comparable<? super T>> - Class in org.deeplearning4j.eval
-
- ConfusionMatrix(List<T>) - Constructor for class org.deeplearning4j.eval.ConfusionMatrix
-
Creates an empty confusion Matrix
- ConfusionMatrix() - Constructor for class org.deeplearning4j.eval.ConfusionMatrix
-
- ConfusionMatrix(ConfusionMatrix<T>) - Constructor for class org.deeplearning4j.eval.ConfusionMatrix
-
Creates a new ConfusionMatrix initialized with the contents of another ConfusionMatrix.
- confusionMatrix() - Method in class org.deeplearning4j.eval.Evaluation
-
Get the confusion matrix as a String
- ConfusionMatrixDeserializer - Class in org.deeplearning4j.eval.serde
-
A JSON deserializer for
ConfusionMatrix<Integer> instances, used in
Evaluation
- ConfusionMatrixDeserializer() - Constructor for class org.deeplearning4j.eval.serde.ConfusionMatrixDeserializer
-
- confusionMatrixMetaData - Variable in class org.deeplearning4j.eval.Evaluation
-
- ConfusionMatrixSerializer - Class in org.deeplearning4j.eval.serde
-
A JSON serializer for
ConfusionMatrix<Integer> instances, used in
Evaluation
- ConfusionMatrixSerializer() - Constructor for class org.deeplearning4j.eval.serde.ConfusionMatrixSerializer
-
- confusionToString() - Method in class org.deeplearning4j.eval.Evaluation
-
Get a String representation of the confusion matrix
- ConjugateGradient - Class in org.deeplearning4j.optimize.solvers
-
Originally based on cc.mallet.optimize.ConjugateGradient
Rewritten based on Conjugate Gradient algorithm in Bengio et al.,
Deep Learning (in preparation) Ch8.
- ConjugateGradient(NeuralNetConfiguration, StepFunction, Collection<TrainingListener>, Model) - Constructor for class org.deeplearning4j.optimize.solvers.ConjugateGradient
-
- ConjugateGradient(NeuralNetConfiguration, StepFunction, Collection<TrainingListener>, Collection<TerminationCondition>, Model) - Constructor for class org.deeplearning4j.optimize.solvers.ConjugateGradient
-
- CONJUGATION_FORM - Static variable in class com.atilika.kuromoji.ipadic.compile.DictionaryEntry
-
- CONJUGATION_TYPE - Static variable in class com.atilika.kuromoji.ipadic.compile.DictionaryEntry
-
- connect(List<Tree>) - Method in class org.deeplearning4j.nn.layers.feedforward.autoencoder.recursive.Tree
-
Connects the given trees
and sets the parents of the children
- CONNECTION_COSTS_FILENAME - Static variable in class com.atilika.kuromoji.dict.ConnectionCosts
-
- ConnectionCosts - Class in com.atilika.kuromoji.dict
-
- ConnectionCosts(int, ShortBuffer) - Constructor for class com.atilika.kuromoji.dict.ConnectionCosts
-
- connectionCosts - Variable in class com.atilika.kuromoji.TokenizerBase.Builder
-
- ConnectionCostsCompiler - Class in com.atilika.kuromoji.compile
-
- ConnectionCostsCompiler(OutputStream) - Constructor for class com.atilika.kuromoji.compile.ConnectionCostsCompiler
-
- ConstantDistribution - Class in org.deeplearning4j.nn.conf.distribution
-
Constant distribution.
- ConstantDistribution(double) - Constructor for class org.deeplearning4j.nn.conf.distribution.ConstantDistribution
-
Create a Constant distribution with given value
- constrainAllParameters(LayerConstraint...) - Method in class org.deeplearning4j.nn.conf.layers.Layer.Builder
-
Set constraints to be applied to this layer.
- constrainAllParameters(LayerConstraint...) - Method in class org.deeplearning4j.nn.conf.NeuralNetConfiguration.Builder
-
Set constraints to be applied to all layers.
- constrainBeta(LayerConstraint...) - Method in class org.deeplearning4j.nn.conf.layers.BatchNormalization.Builder
-
Set constraints to be applied to the beta parameter of this batch normalisation layer.
- constrainBias(LayerConstraint...) - Method in class org.deeplearning4j.nn.conf.layers.Layer.Builder
-
Set constraints to be applied to bias parameters of this layer.
- constrainBias(LayerConstraint...) - Method in class org.deeplearning4j.nn.conf.NeuralNetConfiguration.Builder
-
Set constraints to be applied to all layers.
- constrainGamma(LayerConstraint...) - Method in class org.deeplearning4j.nn.conf.layers.BatchNormalization.Builder
-
Set constraints to be applied to the gamma parameter of this batch normalisation layer.
- constrainInputWeights(LayerConstraint...) - Method in class org.deeplearning4j.nn.conf.layers.BaseRecurrentLayer.Builder
-
Set constraints to be applied to the RNN input weight parameters of this layer.
- constrainPointWise(LayerConstraint...) - Method in class org.deeplearning4j.nn.conf.layers.SeparableConvolution2D.Builder
-
Set constraints to be applied to the point-wise convolution weight parameters of this layer.
- constrainRecurrent(LayerConstraint...) - Method in class org.deeplearning4j.nn.conf.layers.BaseRecurrentLayer.Builder
-
Set constraints to be applied to the RNN recurrent weight parameters of this layer.
- constraints - Variable in class org.deeplearning4j.nn.conf.layers.Layer
-
- constraints(List<LayerConstraint>) - Method in class org.deeplearning4j.nn.transferlearning.FineTuneConfiguration.Builder
-
Set constraints to be applied to all layers.
- constraints - Variable in class org.deeplearning4j.nn.transferlearning.FineTuneConfiguration
-
- constrainWeights(LayerConstraint...) - Method in class org.deeplearning4j.nn.conf.layers.Layer.Builder
-
Set constraints to be applied to the weight parameters of this layer.
- constrainWeights(LayerConstraint...) - Method in class org.deeplearning4j.nn.conf.NeuralNetConfiguration.Builder
-
Set constraints to be applied to all layers.
- consume(InMemoryLookupTable<T>) - Method in class org.deeplearning4j.models.embeddings.inmemory.InMemoryLookupTable
-
This method consumes weights of a given InMemoryLookupTable
PLEASE NOTE: this method explicitly resets current weights
- consumers - Variable in class org.deeplearning4j.optimize.solvers.accumulation.FancyBlockingQueue
-
- consumeVocabulary(VocabularyHolder) - Method in class org.deeplearning4j.models.word2vec.wordstore.VocabularyHolder
-
- consumingTopic - Variable in class org.deeplearning4j.streaming.routes.DL4jServeRouteBuilder
-
- contains(INDArray) - Method in class org.deeplearning4j.clustering.kdtree.HyperRect
-
- contains(double) - Method in class org.deeplearning4j.clustering.kdtree.HyperRect.Interval
-
- contains(INDArray) - Method in class org.deeplearning4j.clustering.sptree.Cell
-
- contains(Object) - Method in class org.deeplearning4j.optimize.solvers.accumulation.FancyBlockingQueue
-
- contains(Object) - Method in class org.deeplearning4j.parallelism.ConcurrentHashSet
-
Deprecated.
- contains(Object) - Method in class org.deeplearning4j.parallelism.MagicQueue
-
Deprecated.
This method isn't supported
- contains(Object) - Method in class org.deeplearning4j.util.DiskBasedQueue
-
- containsAll(Collection<?>) - Method in class org.deeplearning4j.optimize.solvers.accumulation.FancyBlockingQueue
-
- containsAll(Collection<?>) - Method in class org.deeplearning4j.parallelism.ConcurrentHashSet
-
Deprecated.
- containsAll(Collection<?>) - Method in class org.deeplearning4j.parallelism.MagicQueue
-
Deprecated.
This method isn't supported
- containsAll(Collection<?>) - Method in class org.deeplearning4j.util.DiskBasedQueue
-
- containsElement(T) - Method in class org.deeplearning4j.models.word2vec.wordstore.inmemory.AbstractCache
-
Checks, if specified element exists in vocabulary
- containsKey(Object) - Method in class com.atilika.kuromoji.trie.PatriciaTrie
-
Test membership in this trie
- containsKeyPrefix(String) - Method in class com.atilika.kuromoji.trie.PatriciaTrie
-
Test key prefix membership in this trie (prefix search using key)
- containsPoint(INDArray) - Method in class org.deeplearning4j.clustering.quadtree.Cell
-
Whether the given point is contained
within this cell
- containsValue(Object) - Method in class com.atilika.kuromoji.trie.PatriciaTrie
-
Predicate to test value membership
- containsWord(String) - Method in class org.deeplearning4j.models.word2vec.wordstore.inmemory.AbstractCache
-
Checks, if specified label exists in vocabulary
- containsWord(String) - Method in class org.deeplearning4j.models.word2vec.wordstore.inmemory.InMemoryLookupCache
-
Deprecated.
Returns true if the cache contains the given word
- containsWord(String) - Method in interface org.deeplearning4j.models.word2vec.wordstore.VocabCache
-
Returns true if the cache contains the given word
- containsWord(String) - Method in class org.deeplearning4j.models.word2vec.wordstore.VocabularyHolder
-
Checks vocabulary for the word existance
- content(String[][]) - Method in class org.deeplearning4j.ui.components.table.ComponentTable.Builder
-
Content for the table, as 2d String[]
- content - Variable in class org.deeplearning4j.ui.standalone.ComponentObject
-
- context - Variable in class org.deeplearning4j.spark.iterator.SparkADSI
-
- context - Variable in class org.deeplearning4j.spark.iterator.SparkAMDSI
-
- ContextLabelRetriever - Class in org.deeplearning4j.text.movingwindow
-
Context Label Retriever
- conv1x1(int, int, double) - Static method in class org.deeplearning4j.zoo.model.helper.FaceNetHelper
-
- conv3x3(int, int, double) - Static method in class org.deeplearning4j.zoo.model.helper.FaceNetHelper
-
- conv5x5(int, int, double) - Static method in class org.deeplearning4j.zoo.model.helper.FaceNetHelper
-
- conv7x7(int, int, double) - Static method in class org.deeplearning4j.zoo.model.helper.FaceNetHelper
-
- ConvergenceCondition - Class in org.deeplearning4j.clustering.condition
-
- ConvergenceCondition() - Constructor for class org.deeplearning4j.clustering.condition.ConvergenceCondition
-
- convert(Collection<Collection<Writable>>, int) - Method in class org.deeplearning4j.streaming.conversion.dataset.CSVRecordToDataSet
-
- convert(Collection<Collection<Writable>>, int) - Method in interface org.deeplearning4j.streaming.conversion.dataset.RecordToDataSet
-
Converts records in to a dataset
- convert(Collection<Collection<Writable>>) - Method in class org.deeplearning4j.streaming.conversion.ndarray.CSVRecordToINDArray
-
- convert(Collection<Collection<Writable>>) - Method in class org.deeplearning4j.streaming.conversion.ndarray.NDArrayRecordToNDArray
-
- convert(Collection<Collection<Writable>>) - Method in interface org.deeplearning4j.streaming.conversion.ndarray.RecordToNDArray
-
Converts a list of records in to 1 ndarray
- converter - Variable in class org.deeplearning4j.datasets.datavec.RecordReaderDataSetIterator.Builder
-
- converter - Variable in class org.deeplearning4j.datasets.datavec.RecordReaderDataSetIterator
-
- ConvexOptimizer - Interface in org.deeplearning4j.optimize.api
-
Convex optimizer.
- convNxN(int, int, int, int, boolean) - Static method in class org.deeplearning4j.zoo.model.helper.FaceNetHelper
-
- convNxNreduce(int, int, int) - Static method in class org.deeplearning4j.zoo.model.helper.FaceNetHelper
-
- Convolution1D - Class in org.deeplearning4j.nn.conf.layers
-
1D convolution layer
- Convolution1D() - Constructor for class org.deeplearning4j.nn.conf.layers.Convolution1D
-
- Convolution1DLayer - Class in org.deeplearning4j.nn.conf.layers
-
1D (temporal) convolutional layer.
- Convolution1DLayer - Class in org.deeplearning4j.nn.layers.convolution
-
1D (temporal) convolutional layer.
- Convolution1DLayer(NeuralNetConfiguration) - Constructor for class org.deeplearning4j.nn.layers.convolution.Convolution1DLayer
-
- Convolution1DLayer(NeuralNetConfiguration, INDArray) - Constructor for class org.deeplearning4j.nn.layers.convolution.Convolution1DLayer
-
- Convolution1DLayer.Builder - Class in org.deeplearning4j.nn.conf.layers
-
- Convolution2D - Class in org.deeplearning4j.nn.conf.layers
-
2D convolution layer
- Convolution2D() - Constructor for class org.deeplearning4j.nn.conf.layers.Convolution2D
-
- Convolution3D - Class in org.deeplearning4j.nn.conf.layers
-
3D convolution layer configuration
- Convolution3D(Convolution3D.Builder) - Constructor for class org.deeplearning4j.nn.conf.layers.Convolution3D
-
3-dimensional convolutional layer configuration
nIn in the input layer is the number of channels
nOut is the number of filters to be used in the net or in other words the depth
The builder specifies the filter/kernel size, the stride and padding
The pooling layer takes the kernel size
- Convolution3D.Builder - Class in org.deeplearning4j.nn.conf.layers
-
- Convolution3D.DataFormat - Enum in org.deeplearning4j.nn.conf.layers
-
- Convolution3DLayer - Class in org.deeplearning4j.nn.layers.convolution
-
3D convolution layer implementation.
- Convolution3DLayer(NeuralNetConfiguration) - Constructor for class org.deeplearning4j.nn.layers.convolution.Convolution3DLayer
-
- Convolution3DLayer(NeuralNetConfiguration, INDArray) - Constructor for class org.deeplearning4j.nn.layers.convolution.Convolution3DLayer
-
- Convolution3DParamInitializer - Class in org.deeplearning4j.nn.params
-
Initialize 3D convolution parameters.
- Convolution3DParamInitializer() - Constructor for class org.deeplearning4j.nn.params.Convolution3DParamInitializer
-
- Convolution3DUtils - Class in org.deeplearning4j.util
-
Shape utilities for 3D convolution layers
- convolutional(int, int, int) - Static method in class org.deeplearning4j.nn.conf.inputs.InputType
-
Input type for convolutional (CNN) data, that is 4d with shape [miniBatchSize, channels, height, width].
- convolutional(int, int, int) - Method in class org.deeplearning4j.nn.conf.NeuralNetConfiguration.ListBuilder.InputTypeBuilder
-
- convolutional3D(int, int, int, int) - Static method in class org.deeplearning4j.nn.conf.inputs.InputType
-
Input type for 3D convolutional (CNN3D) data, that is 5d with shape
[miniBatchSize, channels, height, width, channels].
- convolutionalFlat(int, int, int) - Static method in class org.deeplearning4j.nn.conf.inputs.InputType
-
Input type for convolutional (CNN) data, where the data is in flattened (row vector) format.
- convolutionalFlat(int, int, int) - Method in class org.deeplearning4j.nn.conf.NeuralNetConfiguration.ListBuilder.InputTypeBuilder
-
- ConvolutionalIterationListener - Class in org.deeplearning4j.ui.weights
-
- ConvolutionalIterationListener(UiConnectionInfo, int) - Constructor for class org.deeplearning4j.ui.weights.ConvolutionalIterationListener
-
- ConvolutionalIterationListener(int) - Constructor for class org.deeplearning4j.ui.weights.ConvolutionalIterationListener
-
- ConvolutionalIterationListener(int, boolean) - Constructor for class org.deeplearning4j.ui.weights.ConvolutionalIterationListener
-
- ConvolutionalIterationListener(StatsStorageRouter, int, boolean) - Constructor for class org.deeplearning4j.ui.weights.ConvolutionalIterationListener
-
- ConvolutionalIterationListener(StatsStorageRouter, int, boolean, String, String) - Constructor for class org.deeplearning4j.ui.weights.ConvolutionalIterationListener
-
- ConvolutionalListenerModule - Class in org.deeplearning4j.ui.module.convolutional
-
Used for plotting results from the ConvolutionalIterationListener
- ConvolutionalListenerModule() - Constructor for class org.deeplearning4j.ui.module.convolutional.ConvolutionalListenerModule
-
- convolutionDim - Variable in class org.deeplearning4j.nn.conf.layers.ConvolutionLayer.BaseConvBuilder
-
- ConvolutionHelper - Interface in org.deeplearning4j.nn.layers.convolution
-
Helper for the convolution layer.
- ConvolutionLayer - Class in org.deeplearning4j.nn.conf.layers
-
- ConvolutionLayer(ConvolutionLayer.BaseConvBuilder<?>) - Constructor for class org.deeplearning4j.nn.conf.layers.ConvolutionLayer
-
ConvolutionLayer
nIn in the input layer is the number of channels
nOut is the number of filters to be used in the net or in other words the channels
The builder specifies the filter/kernel size, the stride and padding
The pooling layer takes the kernel size
- ConvolutionLayer - Class in org.deeplearning4j.nn.layers.convolution
-
Convolution layer
- ConvolutionLayer(NeuralNetConfiguration) - Constructor for class org.deeplearning4j.nn.layers.convolution.ConvolutionLayer
-
- ConvolutionLayer(NeuralNetConfiguration, INDArray) - Constructor for class org.deeplearning4j.nn.layers.convolution.ConvolutionLayer
-
- ConvolutionLayer.AlgoMode - Enum in org.deeplearning4j.nn.conf.layers
-
- ConvolutionLayer.BaseConvBuilder<T extends ConvolutionLayer.BaseConvBuilder<T>> - Class in org.deeplearning4j.nn.conf.layers
-
- ConvolutionLayer.Builder - Class in org.deeplearning4j.nn.conf.layers
-
- ConvolutionLayer.BwdDataAlgo - Enum in org.deeplearning4j.nn.conf.layers
-
- ConvolutionLayer.BwdFilterAlgo - Enum in org.deeplearning4j.nn.conf.layers
-
- ConvolutionLayer.FwdAlgo - Enum in org.deeplearning4j.nn.conf.layers
-
- ConvolutionListenerPersistable - Class in org.deeplearning4j.ui.weights
-
Created by Alex on 24/10/2016.
- ConvolutionListenerPersistable() - Constructor for class org.deeplearning4j.ui.weights.ConvolutionListenerPersistable
-
- ConvolutionMode - Enum in org.deeplearning4j.nn.conf
-
ConvolutionMode defines how convolution operations should be executed for Convolutional and Subsampling layers,
for a given input size and network configuration (specifically stride/padding/kernel sizes).
Currently, 3 modes are provided:
Strict: Output size for Convolutional and Subsampling layers are calculated as follows, in each dimension:
outputSize = (inputSize - kernelSize + 2*padding) / stride + 1.
- convolutionMode(ConvolutionMode) - Method in class org.deeplearning4j.nn.conf.layers.Convolution3D.Builder
-
- convolutionMode - Variable in class org.deeplearning4j.nn.conf.layers.ConvolutionLayer.BaseConvBuilder
-
- convolutionMode(ConvolutionMode) - Method in class org.deeplearning4j.nn.conf.layers.ConvolutionLayer.BaseConvBuilder
-
Set the convolution mode for the Convolution layer.
- convolutionMode - Variable in class org.deeplearning4j.nn.conf.layers.ConvolutionLayer
-
- convolutionMode(ConvolutionMode) - Method in class org.deeplearning4j.nn.conf.layers.Deconvolution2D.Builder
-
Set the convolution mode for the Convolution layer.
- convolutionMode - Variable in class org.deeplearning4j.nn.conf.layers.Subsampling3DLayer.BaseSubsamplingBuilder
-
- convolutionMode(ConvolutionMode) - Method in class org.deeplearning4j.nn.conf.layers.Subsampling3DLayer.BaseSubsamplingBuilder
-
Set the convolution mode for the Convolution layer.
- convolutionMode - Variable in class org.deeplearning4j.nn.conf.layers.Subsampling3DLayer
-
- convolutionMode - Variable in class org.deeplearning4j.nn.conf.layers.SubsamplingLayer.BaseSubsamplingBuilder
-
- convolutionMode(ConvolutionMode) - Method in class org.deeplearning4j.nn.conf.layers.SubsamplingLayer.BaseSubsamplingBuilder
-
Set the convolution mode for the Convolution layer.
- convolutionMode - Variable in class org.deeplearning4j.nn.conf.layers.SubsamplingLayer
-
- convolutionMode - Variable in class org.deeplearning4j.nn.conf.NeuralNetConfiguration.Builder
-
- convolutionMode(ConvolutionMode) - Method in class org.deeplearning4j.nn.conf.NeuralNetConfiguration.Builder
-
Sets the convolution mode for convolutional layers, which impacts padding and output sizes.
- convolutionMode - Variable in class org.deeplearning4j.nn.layers.convolution.ConvolutionLayer
-
- convolutionMode - Variable in class org.deeplearning4j.nn.layers.convolution.subsampling.Subsampling3DLayer
-
- convolutionMode - Variable in class org.deeplearning4j.nn.layers.convolution.subsampling.SubsamplingLayer
-
- convolutionMode(ConvolutionMode) - Method in class org.deeplearning4j.nn.transferlearning.FineTuneConfiguration.Builder
-
Sets the convolution mode for convolutional layers, which impacts padding and output sizes.
- convolutionMode - Variable in class org.deeplearning4j.nn.transferlearning.FineTuneConfiguration
-
- ConvolutionParamInitializer - Class in org.deeplearning4j.nn.params
-
Initialize convolution params.
- ConvolutionParamInitializer() - Constructor for class org.deeplearning4j.nn.params.ConvolutionParamInitializer
-
- ConvolutionUtils - Class in org.deeplearning4j.util
-
Convolutional shape utilities
- CoOccurenceReader<T extends SequenceElement> - Interface in org.deeplearning4j.models.glove.count
-
Created by raver on 24.12.2015.
- CoOccurrenceCalculator - Class in org.deeplearning4j.spark.models.embeddings.glove.cooccurrences
-
Calculate co occurrences based on tokens
- CoOccurrenceCalculator(boolean, Broadcast<VocabCache<VocabWord>>, int) - Constructor for class org.deeplearning4j.spark.models.embeddings.glove.cooccurrences.CoOccurrenceCalculator
-
- CoOccurrenceCounts - Class in org.deeplearning4j.spark.models.embeddings.glove.cooccurrences
-
Co occurrence count reduction
- CoOccurrenceCounts() - Constructor for class org.deeplearning4j.spark.models.embeddings.glove.cooccurrences.CoOccurrenceCounts
-
- coOccurrenceCounts(Broadcast<CounterMap<String, String>>) - Method in class org.deeplearning4j.spark.models.embeddings.glove.GloveParam.Builder
-
- CoOccurrenceWeight<T extends SequenceElement> - Class in org.deeplearning4j.models.glove.count
-
Simple POJO holding pairs of elements and their respective weights, used in GloVe -> CoOccurrence
- CoOccurrenceWeight() - Constructor for class org.deeplearning4j.models.glove.count.CoOccurrenceWeight
-
- CoOccurrenceWriter<T extends SequenceElement> - Interface in org.deeplearning4j.models.glove.count
-
Created by fartovii on 25.12.15.
- coordSplit(double[]) - Static method in class org.deeplearning4j.clustering.util.MathUtils
-
This returns the coordinate split in a list of coordinates
such that the values for ret[0] are the x values
and ret[1] are the y values
- coordSplit(List<Double>) - Static method in class org.deeplearning4j.clustering.util.MathUtils
-
This returns the coordinate split in a list of coordinates
such that the values for ret[0] are the x values
and ret[1] are the y values
- copyWeightsToLayer(Layer) - Method in class org.deeplearning4j.nn.modelimport.keras.KerasLayer
-
Copy Keras layer weights to DL4J Layer.
- copyWeightsToModel(Model, Map<String, KerasLayer>) - Static method in class org.deeplearning4j.nn.modelimport.keras.utils.KerasModelUtils
-
Helper function to import weights from nested Map into existing model.
- corner(int) - Method in class org.deeplearning4j.clustering.sptree.Cell
-
- corner() - Method in class org.deeplearning4j.clustering.sptree.Cell
-
- CORRECT - Static variable in class org.deeplearning4j.models.embeddings.reader.impl.BasicModelUtils
-
- correlation(double[], double[]) - Static method in class org.deeplearning4j.clustering.util.MathUtils
-
Returns the correlation coefficient of two double vectors.
- correlationR2(int) - Method in class org.deeplearning4j.eval.RegressionEvaluation
-
- corruptionLevel(double) - Method in class org.deeplearning4j.nn.conf.layers.AutoEncoder.Builder
-
- corruptionLevel - Variable in class org.deeplearning4j.nn.conf.layers.AutoEncoder
-
- costArray - Variable in class org.deeplearning4j.eval.Evaluation
-
- count - Variable in class org.ansj.dic.LearnTool
-
告诉大家你学习了多少个词了
- count - Static variable in class org.deeplearning4j.models.sequencevectors.transformers.impl.iterables.ParallelTransformerIterator
-
- count() - Method in class org.deeplearning4j.ui.stats.sbe.StaticInfoDecoder.HwDeviceInfoGroupDecoder
-
- count() - Method in class org.deeplearning4j.ui.stats.sbe.StaticInfoDecoder.ModelParamNamesDecoder
-
- count() - Method in class org.deeplearning4j.ui.stats.sbe.StaticInfoDecoder.SwEnvironmentInfoDecoder
-
- count() - Method in class org.deeplearning4j.ui.stats.sbe.StorageMetaDataDecoder.ExtraMetaDataBytesDecoder
-
- count() - Method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder.DataSetMetaDataBytesDecoder
-
- count() - Method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder.DataSetMetaDataBytesDecoder.MetaDataBytesDecoder
-
- count() - Method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder.GcStatsDecoder
-
- count() - Method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder.LayerNamesDecoder
-
- count() - Method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder.MemoryUseDecoder
-
- count() - Method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder.ParamNamesDecoder
-
- count() - Method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder.PerformanceDecoder
-
- count() - Method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder.PerParameterStatsDecoder
-
- count() - Method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder.PerParameterStatsDecoder.HistogramsDecoder
-
- count() - Method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder.PerParameterStatsDecoder.HistogramsDecoder.HistogramCountsDecoder
-
- count() - Method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder.PerParameterStatsDecoder.SummaryStatDecoder
-
- CountCumSum - Class in org.deeplearning4j.spark.text.functions
-
- CountCumSum(JavaRDD<AtomicLong>) - Constructor for class org.deeplearning4j.spark.text.functions.CountCumSum
-
- countDown() - Method in class org.deeplearning4j.models.word2vec.StreamWork
-
- counter - Variable in class org.deeplearning4j.datasets.iterator.DataSetIteratorSplitter
-
- counter - Variable in class org.deeplearning4j.datasets.iterator.MultiDataSetIteratorSplitter
-
- counter - Variable in class org.deeplearning4j.datasets.iterator.parallel.BaseParallelDataSetIterator
-
- counter - Variable in class org.deeplearning4j.models.sequencevectors.transformers.impl.GraphTransformer
-
- counter - Variable in class org.deeplearning4j.spark.models.sequencevectors.learning.elements.SparkSkipGram
-
- countFinished - Variable in class org.deeplearning4j.models.paragraphvectors.ParagraphVectors
-
- CountFunction<T extends SequenceElement> - Class in org.deeplearning4j.spark.models.sequencevectors.functions
-
This accumulator function does count individual elements, using provided Accumulator
- CountFunction(Broadcast<VectorsConfiguration>, Broadcast<VoidConfiguration>, Accumulator<Counter<Long>>, boolean) - Constructor for class org.deeplearning4j.spark.models.sequencevectors.functions.CountFunction
-
- CountMap<T extends SequenceElement> - Class in org.deeplearning4j.models.glove.count
-
Drop-in replacement for CounterMap
WORK IN PROGRESS, PLEASE DO NOT USE
- CountMap() - Constructor for class org.deeplearning4j.models.glove.count.CountMap
-
- CountPartitionsFunction<T> - Class in org.deeplearning4j.spark.impl.common
-
This is a function use to count the number of elements in each partition.
- CountPartitionsFunction() - Constructor for class org.deeplearning4j.spark.impl.common.CountPartitionsFunction
-
- CountsForThreshold(double) - Constructor for class org.deeplearning4j.eval.ROC.CountsForThreshold
-
- countSubmitted - Variable in class org.deeplearning4j.models.paragraphvectors.ParagraphVectors
-
- countTokens() - Method in class org.deeplearning4j.text.tokenization.tokenizer.ChineseTokenizer
-
- countTokens() - Method in class org.deeplearning4j.text.tokenization.tokenizer.DefaultStreamTokenizer
-
Returns number of tokens
PLEASE NOTE: this method effectively preloads all tokens.
- countTokens() - Method in class org.deeplearning4j.text.tokenization.tokenizer.DefaultTokenizer
-
- countTokens() - Method in class org.deeplearning4j.text.tokenization.tokenizer.JapaneseTokenizer
-
- countTokens() - Method in class org.deeplearning4j.text.tokenization.tokenizer.KoreanTokenizer
-
- countTokens() - Method in class org.deeplearning4j.text.tokenization.tokenizer.NGramTokenizer
-
- countTokens() - Method in class org.deeplearning4j.text.tokenization.tokenizer.PosUimaTokenizer
-
- countTokens() - Method in interface org.deeplearning4j.text.tokenization.tokenizer.Tokenizer
-
The number of tokens in the tokenizer
- countTokens() - Method in class org.deeplearning4j.text.tokenization.tokenizer.UimaTokenizer
-
- create() - Method in class org.deeplearning4j.aws.ec2.Ec2BoxCreator
-
Create the instances
- create() - Method in class org.deeplearning4j.bagofwords.vectorizer.DefaultInputStreamCreator
-
- create(int) - Method in class org.deeplearning4j.graph.vertexfactory.IntegerVertexFactory
-
- create(int) - Method in class org.deeplearning4j.graph.vertexfactory.StringVertexFactory
-
- create(int) - Method in interface org.deeplearning4j.graph.vertexfactory.VertexFactory
-
- create(int) - Method in class org.deeplearning4j.graph.vertexfactory.VoidVertexFactory
-
- create(int) - Method in class org.deeplearning4j.models.sequencevectors.graph.vertex.AbstractVertexFactory
-
- create(int, T) - Method in class org.deeplearning4j.models.sequencevectors.graph.vertex.AbstractVertexFactory
-
- create(int) - Method in interface org.deeplearning4j.models.sequencevectors.graph.vertex.VertexFactory
-
- create(int, T) - Method in interface org.deeplearning4j.models.sequencevectors.graph.vertex.VertexFactory
-
- create() - Method in interface org.deeplearning4j.models.word2vec.InputStreamCreator
-
Create an input stream
- create(String, int, Model, int, boolean, ParallelWrapper, WorkspaceMode, int) - Method in class org.deeplearning4j.parallelism.factory.DefaultTrainerContext
-
Create a
Trainer
based on the given parameters
- create(String, int, Model, int, boolean, ParallelWrapper, WorkspaceMode, int) - Method in class org.deeplearning4j.parallelism.factory.SymmetricTrainerContext
-
Create a
Trainer
based on the given parameters
- create(String, int, Model, int, boolean, ParallelWrapper, WorkspaceMode, int) - Method in interface org.deeplearning4j.parallelism.factory.TrainerContext
-
Create a
Trainer
based on the given parameters
- create() - Method in interface org.deeplearning4j.parallelism.main.DataSetIteratorProviderFactory
-
Create an DataSetIterator
- create() - Method in interface org.deeplearning4j.parallelism.main.MultiDataSetProviderFactory
-
Create an MultiDataSetIterator
- create(String, int, Model, int, boolean, ParallelWrapper, WorkspaceMode, int) - Method in class org.deeplearning4j.parallelism.parameterserver.ParameterServerTrainerContext
-
Create a
Trainer
based on the given parameters
- create(String) - Method in class org.deeplearning4j.text.tokenization.tokenizerFactory.ChineseTokenizerFactory
-
- create(InputStream) - Method in class org.deeplearning4j.text.tokenization.tokenizerFactory.ChineseTokenizerFactory
-
- create(String) - Method in class org.deeplearning4j.text.tokenization.tokenizerfactory.DefaultTokenizerFactory
-
- create(InputStream) - Method in class org.deeplearning4j.text.tokenization.tokenizerfactory.DefaultTokenizerFactory
-
- create(String) - Method in class org.deeplearning4j.text.tokenization.tokenizerfactory.JapaneseTokenizerFactory
-
Create a Tokenizer instance for the given sentence.
- create(InputStream) - Method in class org.deeplearning4j.text.tokenization.tokenizerfactory.JapaneseTokenizerFactory
-
InputStreams are currently unsupported.
- create(String) - Method in class org.deeplearning4j.text.tokenization.tokenizerfactory.KoreanTokenizerFactory
-
- create(InputStream) - Method in class org.deeplearning4j.text.tokenization.tokenizerfactory.KoreanTokenizerFactory
-
- create(String) - Method in class org.deeplearning4j.text.tokenization.tokenizerfactory.NGramTokenizerFactory
-
- create(InputStream) - Method in class org.deeplearning4j.text.tokenization.tokenizerfactory.NGramTokenizerFactory
-
- create(String) - Method in class org.deeplearning4j.text.tokenization.tokenizerfactory.PosUimaTokenizerFactory
-
- create(InputStream) - Method in class org.deeplearning4j.text.tokenization.tokenizerfactory.PosUimaTokenizerFactory
-
- create(String) - Method in interface org.deeplearning4j.text.tokenization.tokenizerfactory.TokenizerFactory
-
The tokenizer to createComplex
- create(InputStream) - Method in interface org.deeplearning4j.text.tokenization.tokenizerfactory.TokenizerFactory
-
Create a tokenizer based on an input stream
- create(String) - Method in class org.deeplearning4j.text.tokenization.tokenizerfactory.UimaTokenizerFactory
-
- create(InputStream) - Method in class org.deeplearning4j.text.tokenization.tokenizerfactory.UimaTokenizerFactory
-
- createBias(NeuralNetConfiguration, INDArray, boolean) - Method in class org.deeplearning4j.nn.params.ConvolutionParamInitializer
-
- createBias(NeuralNetConfiguration, INDArray, boolean) - Method in class org.deeplearning4j.nn.params.DefaultParamInitializer
-
- createBias(int, double, INDArray, boolean) - Method in class org.deeplearning4j.nn.params.DefaultParamInitializer
-
- createBias(NeuralNetConfiguration, INDArray, boolean) - Method in class org.deeplearning4j.nn.params.DepthwiseConvolutionParamInitializer
-
- createBias(NeuralNetConfiguration, INDArray, boolean) - Method in class org.deeplearning4j.nn.params.SeparableConvolutionParamInitializer
-
- createCenterLossMatrix(NeuralNetConfiguration, INDArray, boolean) - Method in class org.deeplearning4j.nn.params.CenterLossParamInitializer
-
- createCluster() - Method in class org.deeplearning4j.aws.emr.SparkEMRClient
-
Creates the current cluster
- createConsumer() - Method in class org.deeplearning4j.streaming.kafka.NDArrayKafkaClient
-
- createDepthWiseWeightMatrix(NeuralNetConfiguration, INDArray, boolean) - Method in class org.deeplearning4j.nn.params.DepthwiseConvolutionParamInitializer
-
- createDepthWiseWeightMatrix(NeuralNetConfiguration, INDArray, boolean) - Method in class org.deeplearning4j.nn.params.SeparableConvolutionParamInitializer
-
- createDistribution(Distribution) - Static method in class org.deeplearning4j.nn.conf.distribution.Distributions
-
- createGradient(INDArray, INDArray, INDArray) - Method in class org.deeplearning4j.nn.layers.BasePretrainNetwork
-
- createHandles() - Method in class org.deeplearning4j.nn.layers.BaseCudnnHelper.CudnnContext
-
- createPointWiseWeightMatrix(NeuralNetConfiguration, INDArray, boolean) - Method in class org.deeplearning4j.nn.params.SeparableConvolutionParamInitializer
-
- createPublisher() - Method in class org.deeplearning4j.streaming.kafka.NDArrayKafkaClient
-
- createSpot() - Method in class org.deeplearning4j.aws.ec2.Ec2BoxCreator
-
- createStepFunction(StepFunction) - Static method in class org.deeplearning4j.optimize.stepfunctions.StepFunctions
-
- createToken(int, String, ViterbiNode.Type, int, Dictionary) - Method in interface com.atilika.kuromoji.viterbi.TokenFactory
-
- createTokenList(String) - Method in class com.atilika.kuromoji.TokenizerBase
-
Tokenizes the provided text and returns a list of tokens with various feature information
- createVisibleBias(NeuralNetConfiguration, INDArray, boolean) - Method in class org.deeplearning4j.nn.params.PretrainParamInitializer
-
- createWeightMatrix(NeuralNetConfiguration, INDArray, boolean) - Method in class org.deeplearning4j.nn.layers.ocnn.OCNNParamInitializer
-
- createWeightMatrix(NeuralNetConfiguration, INDArray, boolean) - Method in class org.deeplearning4j.nn.params.Convolution3DParamInitializer
-
- createWeightMatrix(NeuralNetConfiguration, INDArray, boolean) - Method in class org.deeplearning4j.nn.params.ConvolutionParamInitializer
-
- createWeightMatrix(NeuralNetConfiguration, INDArray, boolean) - Method in class org.deeplearning4j.nn.params.DeconvolutionParamInitializer
-
- createWeightMatrix(NeuralNetConfiguration, INDArray, boolean) - Method in class org.deeplearning4j.nn.params.DefaultParamInitializer
-
- createWeightMatrix(int, int, WeightInit, Distribution, INDArray, boolean) - Method in class org.deeplearning4j.nn.params.DefaultParamInitializer
-
- createWeightMatrix(int, int, WeightInit, Distribution, INDArray, boolean) - Method in class org.deeplearning4j.nn.params.ElementWiseParamInitializer
-
- createWithPath(String) - Static method in class org.deeplearning4j.text.sentenceiterator.labelaware.LabelAwareUimaSentenceIterator
-
Creates a uima sentence iterator with the given path
- createWithPath(String) - Static method in class org.deeplearning4j.text.sentenceiterator.UimaSentenceIterator
-
Creates a uima sentence iterator with the given path
- creds - Variable in class org.deeplearning4j.aws.s3.BaseS3
-
- CrfLibrary - Class in org.ansj.library
-
- CrfLibrary() - Constructor for class org.ansj.library.CrfLibrary
-
- CRFModel - Class in org.ansj.app.crf.model
-
加载ansj格式的crfmodel,目前此model格式是通过crf++ 或者wapiti生成的
- CRFModel() - Constructor for class org.ansj.app.crf.model.CRFModel
-
- CRFppTxtModel - Class in org.ansj.app.crf.model
-
加载CRF+生成的crf文本模型,测试使用的CRF++版本为:CRF++-0.58
下载地址:https://taku910.github.io/crfpp/#download 在这里感谢作者所做的工作.
- CRFppTxtModel() - Constructor for class org.ansj.app.crf.model.CRFppTxtModel
-
- Cropping1D - Class in org.deeplearning4j.nn.conf.layers.convolutional
-
Cropping layer for convolutional (1d) neural networks.
- Cropping1D(int) - Constructor for class org.deeplearning4j.nn.conf.layers.convolutional.Cropping1D
-
- Cropping1D(int, int) - Constructor for class org.deeplearning4j.nn.conf.layers.convolutional.Cropping1D
-
- Cropping1D(int[]) - Constructor for class org.deeplearning4j.nn.conf.layers.convolutional.Cropping1D
-
- Cropping1D(Cropping1D.Builder) - Constructor for class org.deeplearning4j.nn.conf.layers.convolutional.Cropping1D
-
- Cropping1D.Builder - Class in org.deeplearning4j.nn.conf.layers.convolutional
-
- Cropping1DLayer - Class in org.deeplearning4j.nn.layers.convolution
-
Zero cropping layer for 1D convolutional neural networks.
- Cropping1DLayer(NeuralNetConfiguration) - Constructor for class org.deeplearning4j.nn.layers.convolution.Cropping1DLayer
-
- Cropping2D - Class in org.deeplearning4j.nn.conf.layers.convolutional
-
Cropping layer for convolutional (2d) neural networks.
- Cropping2D(int, int) - Constructor for class org.deeplearning4j.nn.conf.layers.convolutional.Cropping2D
-
- Cropping2D(int, int, int, int) - Constructor for class org.deeplearning4j.nn.conf.layers.convolutional.Cropping2D
-
- Cropping2D(int[]) - Constructor for class org.deeplearning4j.nn.conf.layers.convolutional.Cropping2D
-
- Cropping2D(Cropping2D.Builder) - Constructor for class org.deeplearning4j.nn.conf.layers.convolutional.Cropping2D
-
- Cropping2D.Builder - Class in org.deeplearning4j.nn.conf.layers.convolutional
-
- Cropping2DLayer - Class in org.deeplearning4j.nn.layers.convolution
-
Zero cropping layer for convolutional neural networks.
- Cropping2DLayer(NeuralNetConfiguration) - Constructor for class org.deeplearning4j.nn.layers.convolution.Cropping2DLayer
-
- Cropping3D - Class in org.deeplearning4j.nn.conf.layers.convolutional
-
Cropping layer for convolutional (3d) neural networks.
- Cropping3D(int, int, int) - Constructor for class org.deeplearning4j.nn.conf.layers.convolutional.Cropping3D
-
- Cropping3D(int, int, int, int, int, int) - Constructor for class org.deeplearning4j.nn.conf.layers.convolutional.Cropping3D
-
- Cropping3D(int[]) - Constructor for class org.deeplearning4j.nn.conf.layers.convolutional.Cropping3D
-
- Cropping3D(Cropping3D.Builder) - Constructor for class org.deeplearning4j.nn.conf.layers.convolutional.Cropping3D
-
- Cropping3D.Builder - Class in org.deeplearning4j.nn.conf.layers.convolutional
-
- Cropping3DLayer - Class in org.deeplearning4j.nn.layers.convolution
-
Cropping layer for 3D convolutional neural networks.
- Cropping3DLayer(NeuralNetConfiguration) - Constructor for class org.deeplearning4j.nn.layers.convolution.Cropping3DLayer
-
- CSVReader(File) - Constructor for class org.deeplearning4j.models.embeddings.loader.WordVectorSerializer.CSVReader
-
- CSVRecord - Class in org.deeplearning4j.nearestneighbor.model
-
Created by agibsonccc on 12/24/16.
- CSVRecord() - Constructor for class org.deeplearning4j.nearestneighbor.model.CSVRecord
-
- CSVRecordToDataSet - Class in org.deeplearning4j.streaming.conversion.dataset
-
Assumes csv format and converts a batch of records in to a
size() x record length matrix.
- CSVRecordToDataSet() - Constructor for class org.deeplearning4j.streaming.conversion.dataset.CSVRecordToDataSet
-
- CSVRecordToINDArray - Class in org.deeplearning4j.streaming.conversion.ndarray
-
Assumes csv format and converts a batch of records in to a
size() x record length matrix.
- CSVRecordToINDArray() - Constructor for class org.deeplearning4j.streaming.conversion.ndarray.CSVRecordToINDArray
-
- cudnnAlgoMode - Variable in class org.deeplearning4j.nn.conf.layers.ConvolutionLayer.BaseConvBuilder
-
- cudnnAlgoMode(ConvolutionLayer.AlgoMode) - Method in class org.deeplearning4j.nn.conf.layers.ConvolutionLayer.BaseConvBuilder
-
Defaults to "PREFER_FASTEST", but "NO_WORKSPACE" uses less memory.
- cudnnAlgoMode - Variable in class org.deeplearning4j.nn.conf.layers.ConvolutionLayer
-
Defaults to "PREFER_FASTEST", but "NO_WORKSPACE" uses less memory.
- cudnnAlgoMode - Variable in class org.deeplearning4j.nn.conf.NeuralNetConfiguration.Builder
-
- cudnnAlgoMode(ConvolutionLayer.AlgoMode) - Method in class org.deeplearning4j.nn.conf.NeuralNetConfiguration.Builder
-
Sets the cuDNN algo mode for convolutional layers, which impacts performance and memory usage of cuDNN.
- cudnnAlgoMode(ConvolutionLayer.AlgoMode) - Method in class org.deeplearning4j.nn.transferlearning.FineTuneConfiguration.Builder
-
Sets the cuDNN algo mode for convolutional layers, which impacts performance and memory usage of cuDNN.
- cudnnAlgoMode - Variable in class org.deeplearning4j.nn.transferlearning.FineTuneConfiguration
-
- cudnnAllowFallback - Variable in class org.deeplearning4j.nn.conf.layers.ConvolutionLayer.BaseConvBuilder
-
- cudnnAllowFallback(boolean) - Method in class org.deeplearning4j.nn.conf.layers.ConvolutionLayer.BaseConvBuilder
-
When using CuDNN and an error is encountered, should fallback to the non-CuDNN implementatation be allowed?
If set to false, an exception in CuDNN will be propagated back to the user.
- cudnnAllowFallback - Variable in class org.deeplearning4j.nn.conf.layers.ConvolutionLayer
-
- cudnnAllowFallback - Variable in class org.deeplearning4j.nn.conf.layers.Subsampling3DLayer.BaseSubsamplingBuilder
-
- cudnnAllowFallback(boolean) - Method in class org.deeplearning4j.nn.conf.layers.Subsampling3DLayer.BaseSubsamplingBuilder
-
When using CuDNN and an error is encountered, should fallback to the non-CuDNN implementatation be allowed?
If set to false, an exception in CuDNN will be propagated back to the user.
- cudnnAllowFallback - Variable in class org.deeplearning4j.nn.conf.layers.Subsampling3DLayer
-
- cudnnAllowFallback - Variable in class org.deeplearning4j.nn.conf.layers.SubsamplingLayer.BaseSubsamplingBuilder
-
- cudnnAllowFallback(boolean) - Method in class org.deeplearning4j.nn.conf.layers.SubsamplingLayer.BaseSubsamplingBuilder
-
When using CuDNN and an error is encountered, should fallback to the non-CuDNN implementatation be allowed?
If set to false, an exception in CuDNN will be propagated back to the user.
- cudnnAllowFallback - Variable in class org.deeplearning4j.nn.conf.layers.SubsamplingLayer
-
- CudnnBatchNormalizationHelper - Class in org.deeplearning4j.nn.layers.normalization
-
cuDNN-based helper for the batch normalization layer.
- CudnnBatchNormalizationHelper() - Constructor for class org.deeplearning4j.nn.layers.normalization.CudnnBatchNormalizationHelper
-
- cudnnBwdDataAlgo - Variable in class org.deeplearning4j.nn.conf.layers.ConvolutionLayer.BaseConvBuilder
-
- cudnnBwdDataAlgo - Variable in class org.deeplearning4j.nn.conf.layers.ConvolutionLayer
-
- cudnnBwdDataMode(ConvolutionLayer.BwdDataAlgo) - Method in class org.deeplearning4j.nn.conf.layers.ConvolutionLayer.BaseConvBuilder
-
- cudnnBwdFilterAlgo - Variable in class org.deeplearning4j.nn.conf.layers.ConvolutionLayer.BaseConvBuilder
-
- cudnnBwdFilterAlgo - Variable in class org.deeplearning4j.nn.conf.layers.ConvolutionLayer
-
- cudnnBwdFilterMode(ConvolutionLayer.BwdFilterAlgo) - Method in class org.deeplearning4j.nn.conf.layers.ConvolutionLayer.BaseConvBuilder
-
- CudnnContext() - Constructor for class org.deeplearning4j.nn.layers.BaseCudnnHelper.CudnnContext
-
- CudnnContext(BaseCudnnHelper.CudnnContext) - Constructor for class org.deeplearning4j.nn.layers.BaseCudnnHelper.CudnnContext
-
- CudnnConvolutionHelper - Class in org.deeplearning4j.nn.layers.convolution
-
cuDNN-based helper for the convolution layer.
- CudnnConvolutionHelper() - Constructor for class org.deeplearning4j.nn.layers.convolution.CudnnConvolutionHelper
-
- CudnnConvolutionHelper.CudnnForwardArgs - Class in org.deeplearning4j.nn.layers.convolution
-
- CudnnForwardArgs() - Constructor for class org.deeplearning4j.nn.layers.convolution.CudnnConvolutionHelper.CudnnForwardArgs
-
- cudnnFwdAlgo - Variable in class org.deeplearning4j.nn.conf.layers.ConvolutionLayer.BaseConvBuilder
-
- cudnnFwdAlgo - Variable in class org.deeplearning4j.nn.conf.layers.ConvolutionLayer
-
- cudnnFwdMode(ConvolutionLayer.FwdAlgo) - Method in class org.deeplearning4j.nn.conf.layers.ConvolutionLayer.BaseConvBuilder
-
- CudnnLocalResponseNormalizationHelper - Class in org.deeplearning4j.nn.layers.normalization
-
cuDNN-based helper for the local response normalization layer.
- CudnnLocalResponseNormalizationHelper() - Constructor for class org.deeplearning4j.nn.layers.normalization.CudnnLocalResponseNormalizationHelper
-
- CudnnLSTMHelper - Class in org.deeplearning4j.nn.layers.recurrent
-
cuDNN-based helper for the recurrent LSTM layer (no peephole connections).
- CudnnLSTMHelper() - Constructor for class org.deeplearning4j.nn.layers.recurrent.CudnnLSTMHelper
-
- CudnnSubsamplingHelper - Class in org.deeplearning4j.nn.layers.convolution.subsampling
-
cuDNN-based helper for the subsampling layer.
- CudnnSubsamplingHelper() - Constructor for class org.deeplearning4j.nn.layers.convolution.subsampling.CudnnSubsamplingHelper
-
- cumSumBetweenPartition() - Method in class org.deeplearning4j.spark.text.functions.CountCumSum
-
- cumSumWithinPartition() - Method in class org.deeplearning4j.spark.text.functions.CountCumSum
-
- currBucket() - Method in class org.deeplearning4j.aws.s3.reader.BaseS3DataSetIterator
-
- currentConsumers - Variable in class org.deeplearning4j.optimize.solvers.accumulation.EncodedGradientsAccumulator
-
- currentConsumers - Variable in class org.deeplearning4j.optimize.solvers.accumulation.FancyBlockingQueue
-
- currentFile - Variable in class org.deeplearning4j.text.sentenceiterator.FileSentenceIterator
-
- currentIterator - Variable in class org.deeplearning4j.models.sequencevectors.transformers.impl.SentenceTransformer
-
- currentIterator - Variable in class org.deeplearning4j.text.documentiterator.SimpleLabelAwareIterator
-
- currentLabel() - Method in interface org.deeplearning4j.text.documentiterator.LabelAwareDocumentIterator
-
Returns the current label
- currentLabel() - Method in class org.deeplearning4j.text.sentenceiterator.labelaware.LabelAwareFileSentenceIterator
-
- currentLabel() - Method in interface org.deeplearning4j.text.sentenceiterator.labelaware.LabelAwareSentenceIterator
-
Returns the current label for nextSentence()
- currentLabel() - Method in class org.deeplearning4j.text.sentenceiterator.labelaware.LabelAwareUimaSentenceIterator
-
Returns the current label for nextSentence()
- currentLabels() - Method in class org.deeplearning4j.text.sentenceiterator.labelaware.LabelAwareFileSentenceIterator
-
- currentLabels() - Method in interface org.deeplearning4j.text.sentenceiterator.labelaware.LabelAwareSentenceIterator
-
For multi label problems
- currentLabels() - Method in class org.deeplearning4j.text.sentenceiterator.labelaware.LabelAwareUimaSentenceIterator
-
- currentStep - Variable in class org.deeplearning4j.optimize.solvers.accumulation.FancyBlockingQueue
-
- currentThreshold - Variable in class org.deeplearning4j.optimize.solvers.accumulation.EncodingHandler
-
- currentTimeMillis() - Method in class org.deeplearning4j.spark.time.NTPTimeSource
-
- currentTimeMillis() - Method in class org.deeplearning4j.spark.time.SystemClockTimeSource
-
- currentTimeMillis() - Method in interface org.deeplearning4j.spark.time.TimeSource
-
Get the current time in milliseconds, according to this TimeSource
- currIndex - Variable in class org.deeplearning4j.models.embeddings.inmemory.InMemoryLookupTable.WeightIterator
-
- currLineIterator - Variable in class org.deeplearning4j.text.sentenceiterator.FileSentenceIterator
-
- cursor() - Method in class org.deeplearning4j.datasets.datavec.RecordReaderDataSetIterator
-
- cursor() - Method in class org.deeplearning4j.datasets.datavec.SequenceRecordReaderDataSetIterator
-
- cursor() - Method in class org.deeplearning4j.datasets.iterator.AbstractDataSetIterator
-
The current cursor if applicable
- cursor() - Method in class org.deeplearning4j.datasets.iterator.AsyncDataSetIterator
-
The current cursor if applicable
- cursor() - Method in class org.deeplearning4j.datasets.iterator.AsyncShieldDataSetIterator
-
The current cursor if applicable
- cursor() - Method in class org.deeplearning4j.datasets.iterator.BaseDatasetIterator
-
- cursor() - Method in interface org.deeplearning4j.datasets.iterator.DataSetFetcher
-
Deprecated.
Direct access to a number represenative of iterating through a dataset
- cursor() - Method in class org.deeplearning4j.datasets.iterator.EarlyTerminationDataSetIterator
-
- cursor() - Method in class org.deeplearning4j.datasets.iterator.ExistingDataSetIterator
-
- cursor() - Method in class org.deeplearning4j.datasets.iterator.file.FileDataSetIterator
-
- cursor() - Method in class org.deeplearning4j.datasets.iterator.FileSplitDataSetIterator
-
- cursor() - Method in class org.deeplearning4j.datasets.iterator.impl.BenchmarkDataSetIterator
-
- cursor() - Method in class org.deeplearning4j.datasets.iterator.impl.ListDataSetIterator
-
- cursor() - Method in class org.deeplearning4j.datasets.iterator.IteratorDataSetIterator
-
- cursor() - Method in class org.deeplearning4j.datasets.iterator.MultiDataSetWrapperIterator
-
- cursor() - Method in class org.deeplearning4j.datasets.iterator.MultipleEpochsIterator
-
Deprecated.
The current cursor if applicable
- cursor() - Method in class org.deeplearning4j.datasets.iterator.parallel.BaseParallelDataSetIterator
-
- cursor() - Method in class org.deeplearning4j.datasets.iterator.ReconstructionDataSetIterator
-
The current cursor if applicable
- cursor() - Method in class org.deeplearning4j.datasets.iterator.SamplingDataSetIterator
-
- cursor() - Method in class org.deeplearning4j.datasets.iterator.WorkspacesShieldDataSetIterator
-
- cursor() - Method in class org.deeplearning4j.datasets.test.TestDataSetIterator
-
- cursor() - Method in class org.deeplearning4j.iterator.CnnSentenceDataSetIterator
-
- cursor() - Method in class org.deeplearning4j.models.word2vec.iterator.Word2VecDataFetcher
-
- cursor() - Method in class org.deeplearning4j.models.word2vec.iterator.Word2VecDataSetIterator
-
- cursor - Variable in class org.deeplearning4j.spark.iterator.BaseDataSetIterator
-
- cursor() - Method in class org.deeplearning4j.spark.iterator.BaseDataSetIterator
-
- cursor() - Method in class org.deeplearning4j.spark.parameterserver.iterators.VirtualDataSetIterator
-
- CUSTOM_REGISTRATION_PROPERTY - Static variable in class org.deeplearning4j.nn.conf.serde.JsonMappers
-
- CustomStemmingPreprocessor - Class in org.deeplearning4j.text.tokenization.tokenizer.preprocessor
-
This is StemmingPreprocessor compatible with different StemmingProcessors defined as lucene/tartarus SnowballProgram
such as: RussianStemmer, DutchStemmer, FrenchStemmer etc.
- CustomStemmingPreprocessor(SnowballProgram) - Constructor for class org.deeplearning4j.text.tokenization.tokenizer.preprocessor.CustomStemmingPreprocessor
-
- cut(char[]) - Method in class org.ansj.app.crf.SplitWord
-
- cut(String) - Method in class org.ansj.app.crf.SplitWord
-
- dampingFactor - Variable in class org.deeplearning4j.nn.conf.MultiLayerConfiguration.Builder
-
- Darknet19 - Class in org.deeplearning4j.zoo.model
-
Darknet19
Reference: https://arxiv.org/pdf/1612.08242.pdf
- DarknetHelper - Class in org.deeplearning4j.zoo.model.helper
-
- DarknetHelper() - Constructor for class org.deeplearning4j.zoo.model.helper.DarknetHelper
-
- DarknetLabels - Class in org.deeplearning4j.zoo.util.darknet
-
Helper class that returns label descriptions for Darknet models trained with ImageNet.
- DarknetLabels() - Constructor for class org.deeplearning4j.zoo.util.darknet.DarknetLabels
-
Calls this(true).
- DarknetLabels(boolean) - Constructor for class org.deeplearning4j.zoo.util.darknet.DarknetLabels
-
- data(SparkContext) - Method in interface org.deeplearning4j.spark.data.DataSetProvider
-
Return an rdd of type dataset
- data(SparkContext) - Method in interface org.deeplearning4j.spark.data.MultiDataSetProvider
-
Return an rdd of type dataset
- DataCache() - Constructor for class org.deeplearning4j.nn.layers.BaseCudnnHelper.DataCache
-
- DataCache(long) - Constructor for class org.deeplearning4j.nn.layers.BaseCudnnHelper.DataCache
-
- DataCache(BaseCudnnHelper.DataCache) - Constructor for class org.deeplearning4j.nn.layers.BaseCudnnHelper.DataCache
-
- dataFormat(Convolution3D.DataFormat) - Method in class org.deeplearning4j.nn.conf.layers.Convolution3D.Builder
-
- dataFormat - Variable in class org.deeplearning4j.nn.conf.layers.SpaceToDepthLayer.Builder
-
- dataFormat(SpaceToDepthLayer.DataFormat) - Method in class org.deeplearning4j.nn.conf.layers.SpaceToDepthLayer.Builder
-
- dataFormat - Variable in class org.deeplearning4j.nn.conf.layers.SpaceToDepthLayer
-
- DataPoint - Class in org.deeplearning4j.clustering.sptree
-
A vector with an index and function for distance
- DataPoint(int, INDArray, boolean) - Constructor for class org.deeplearning4j.clustering.sptree.DataPoint
-
- DataPoint(int, INDArray, String, boolean) - Constructor for class org.deeplearning4j.clustering.sptree.DataPoint
-
- DataPoint(int, INDArray) - Constructor for class org.deeplearning4j.clustering.sptree.DataPoint
-
- DataPoint(int, INDArray, String) - Constructor for class org.deeplearning4j.clustering.sptree.DataPoint
-
- dataSet - Variable in class org.deeplearning4j.datasets.iterator.impl.EmnistDataSetIterator
-
- DataSetCallback - Interface in org.deeplearning4j.datasets.iterator.callbacks
-
- DataSetDeserializationCallback - Class in org.deeplearning4j.spark.parameterserver.callbacks
-
- DataSetDeserializationCallback() - Constructor for class org.deeplearning4j.spark.parameterserver.callbacks.DataSetDeserializationCallback
-
- DataSetDeserializer - Class in org.deeplearning4j.datasets.iterator.callbacks
-
This callback does DataSet deserialization of a given file.
- DataSetDeserializer() - Constructor for class org.deeplearning4j.datasets.iterator.callbacks.DataSetDeserializer
-
- DataSetExportFunction - Class in org.deeplearning4j.spark.data
-
A function (used in forEachPartition) to save DataSet objects to disk/HDFS.
- DataSetExportFunction(URI) - Constructor for class org.deeplearning4j.spark.data.DataSetExportFunction
-
- DataSetFetcher - Interface in org.deeplearning4j.datasets.iterator
-
- DataSetIteratorProviderFactory - Interface in org.deeplearning4j.parallelism.main
-
Create a dataset iterator.
- DataSetIteratorSplitter - Class in org.deeplearning4j.datasets.iterator
-
This iterator virtually splits given MultiDataSetIterator into Train and Test parts.
- DataSetIteratorSplitter(DataSetIterator, long, double) - Constructor for class org.deeplearning4j.datasets.iterator.DataSetIteratorSplitter
-
- DataSetLoader - Class in org.deeplearning4j.aws.dataset
-
- DataSetLoader() - Constructor for class org.deeplearning4j.aws.dataset.DataSetLoader
-
- DataSetLossCalculator - Class in org.deeplearning4j.earlystopping.scorecalc
-
Given a DataSetIterator: calculate the total loss for the model on that data set.
- DataSetLossCalculator(DataSetIterator, boolean) - Constructor for class org.deeplearning4j.earlystopping.scorecalc.DataSetLossCalculator
-
Calculate the score (loss function value) on a given data set (usually a test set)
- DataSetLossCalculator(MultiDataSetIterator, boolean) - Constructor for class org.deeplearning4j.earlystopping.scorecalc.DataSetLossCalculator
-
Calculate the score (loss function value) on a given data set (usually a test set)
- DataSetLossCalculatorCG - Class in org.deeplearning4j.earlystopping.scorecalc
-
- DataSetLossCalculatorCG(DataSetIterator, boolean) - Constructor for class org.deeplearning4j.earlystopping.scorecalc.DataSetLossCalculatorCG
-
Deprecated.
Calculate the score (loss function value) on a given data set (usually a test set)
- DataSetLossCalculatorCG(MultiDataSetIterator, boolean) - Constructor for class org.deeplearning4j.earlystopping.scorecalc.DataSetLossCalculatorCG
-
Deprecated.
Calculate the score (loss function value) on a given data set (usually a test set)
- dataSetMetaDataBytes() - Method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder
-
- dataSetMetaDataBytesCount(int) - Method in class org.deeplearning4j.ui.stats.sbe.UpdateEncoder
-
- DataSetMetaDataBytesDecoder() - Constructor for class org.deeplearning4j.ui.stats.sbe.UpdateDecoder.DataSetMetaDataBytesDecoder
-
- dataSetMetaDataBytesDecoderId() - Static method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder
-
- DataSetMetaDataBytesEncoder() - Constructor for class org.deeplearning4j.ui.stats.sbe.UpdateEncoder.DataSetMetaDataBytesEncoder
-
- dataSetMetaDataBytesId() - Static method in class org.deeplearning4j.ui.stats.sbe.UpdateEncoder
-
- dataSetMetaDataClassName() - Method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder
-
- dataSetMetaDataClassName(String) - Method in class org.deeplearning4j.ui.stats.sbe.UpdateEncoder
-
- dataSetMetaDataClassNameCharacterEncoding() - Static method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder
-
- dataSetMetaDataClassNameCharacterEncoding() - Static method in class org.deeplearning4j.ui.stats.sbe.UpdateEncoder
-
- dataSetMetaDataClassNameHeaderLength() - Static method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder
-
- dataSetMetaDataClassNameHeaderLength() - Static method in class org.deeplearning4j.ui.stats.sbe.UpdateEncoder
-
- dataSetMetaDataClassNameId() - Static method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder
-
- dataSetMetaDataClassNameId() - Static method in class org.deeplearning4j.ui.stats.sbe.UpdateEncoder
-
- dataSetMetaDataClassNameLength() - Method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder
-
- dataSetMetaDataClassNameMetaAttribute(MetaAttribute) - Static method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder
-
- dataSetMetaDataClassNameMetaAttribute(MetaAttribute) - Static method in class org.deeplearning4j.ui.stats.sbe.UpdateEncoder
-
- dataSetMetaDataPresent() - Method in class org.deeplearning4j.ui.stats.sbe.UpdateFieldsPresentDecoder
-
- dataSetMetaDataPresent(boolean) - Method in class org.deeplearning4j.ui.stats.sbe.UpdateFieldsPresentEncoder
-
- dataSetName(DataSetType) - Method in class org.deeplearning4j.datasets.fetchers.CacheableExtractableDataSetFetcher
-
- dataSetName(DataSetType) - Method in class org.deeplearning4j.datasets.fetchers.SvhnDataFetcher
-
- dataSetObjectSizeExamples - Variable in class org.deeplearning4j.spark.api.WorkerConfiguration
-
- DataSetOrdering - Class in org.deeplearning4j.spark.ordering
-
Orders by data set size.
- DataSetOrdering() - Constructor for class org.deeplearning4j.spark.ordering.DataSetOrdering
-
- dataSetPreProcessor(DataSetPreProcessor) - Method in class org.deeplearning4j.iterator.CnnSentenceDataSetIterator.Builder
-
Optional DataSetPreProcessor
- DataSetProvider - Interface in org.deeplearning4j.spark.data
-
A provider for an DataSet
rdd.
- DataSets - Class in org.deeplearning4j.datasets
-
- dataSetStreams - Variable in class org.deeplearning4j.spark.iterator.BaseDataSetIterator
-
- DataSetToMultiDataSetFn - Class in org.deeplearning4j.spark.impl.graph.dataset
-
Convert a JavaRDD<DataSet> to a JavaRDD<MultiDataSet>
- DataSetToMultiDataSetFn() - Constructor for class org.deeplearning4j.spark.impl.graph.dataset.DataSetToMultiDataSetFn
-
- DataSetType - Enum in org.deeplearning4j.datasets.fetchers
-
Specify whether train, test, or validation.
- dataType - Variable in class org.deeplearning4j.nn.layers.BaseCudnnHelper
-
- dataTypeSize - Variable in class org.deeplearning4j.nn.layers.BaseCudnnHelper
-
- dataTypeUnMarshal(String) - Method in class org.deeplearning4j.streaming.routes.CamelKafkaRouteBuilder.Builder
-
- DataVecByteDataSetFunction - Class in org.deeplearning4j.spark.datavec
-
- DataVecByteDataSetFunction(int, int, int, int) - Constructor for class org.deeplearning4j.spark.datavec.DataVecByteDataSetFunction
-
- DataVecByteDataSetFunction(int, int, int, int, boolean) - Constructor for class org.deeplearning4j.spark.datavec.DataVecByteDataSetFunction
-
- DataVecByteDataSetFunction(int, int, int, int, boolean, DataSetPreProcessor) - Constructor for class org.deeplearning4j.spark.datavec.DataVecByteDataSetFunction
-
- DataVecDataSetFunction - Class in org.deeplearning4j.spark.datavec
-
Map Collection<Writable> objects (out of a datavec-spark record reader function) to DataSet objects for Spark training.
- DataVecDataSetFunction(int, int, boolean) - Constructor for class org.deeplearning4j.spark.datavec.DataVecDataSetFunction
-
- DataVecDataSetFunction(int, int, boolean, DataSetPreProcessor, WritableConverter) - Constructor for class org.deeplearning4j.spark.datavec.DataVecDataSetFunction
-
- DataVecDataSetFunction(int, int, int, boolean, DataSetPreProcessor, WritableConverter) - Constructor for class org.deeplearning4j.spark.datavec.DataVecDataSetFunction
-
Main constructor, including for multi-label regression
- datavecMarshaller(String) - Method in class org.deeplearning4j.streaming.routes.CamelKafkaRouteBuilder.Builder
-
- DataVecRecord - Class in org.deeplearning4j.spark.datavec.iterator
-
- DataVecRecord() - Constructor for class org.deeplearning4j.spark.datavec.iterator.DataVecRecord
-
- DataVecRecords - Class in org.deeplearning4j.spark.datavec.iterator
-
- DataVecRecords() - Constructor for class org.deeplearning4j.spark.datavec.iterator.DataVecRecords
-
- DataVecSequenceDataSetFunction - Class in org.deeplearning4j.spark.datavec
-
Map Collection<Collection<Writable>> objects (out of a datavec-spark sequence record reader function) to
DataSet objects for Spark training.
- DataVecSequenceDataSetFunction(int, int, boolean) - Constructor for class org.deeplearning4j.spark.datavec.DataVecSequenceDataSetFunction
-
- DataVecSequenceDataSetFunction(int, int, boolean, DataSetPreProcessor, WritableConverter) - Constructor for class org.deeplearning4j.spark.datavec.DataVecSequenceDataSetFunction
-
- DataVecSequencePairDataSetFunction - Class in org.deeplearning4j.spark.datavec
-
Map Tuple2<Collection<Collection<Writable>>,Collection<Collection<Writable>> objects (out of a TWO datavec-spark
sequence record reader functions) to DataSet objects for Spark training.
- DataVecSequencePairDataSetFunction() - Constructor for class org.deeplearning4j.spark.datavec.DataVecSequencePairDataSetFunction
-
Constructor for equal length and no conversion of labels (i.e., regression or already in one-hot representation).
- DataVecSequencePairDataSetFunction(int, boolean) - Constructor for class org.deeplearning4j.spark.datavec.DataVecSequencePairDataSetFunction
-
Constructor for equal length, no data set preprocessor or writable converter
- DataVecSequencePairDataSetFunction(int, boolean, DataVecSequencePairDataSetFunction.AlignmentMode) - Constructor for class org.deeplearning4j.spark.datavec.DataVecSequencePairDataSetFunction
-
Constructor for data with a specified alignment mode, no data set preprocessor or writable converter
- DataVecSequencePairDataSetFunction(int, boolean, DataVecSequencePairDataSetFunction.AlignmentMode, DataSetPreProcessor, WritableConverter) - Constructor for class org.deeplearning4j.spark.datavec.DataVecSequencePairDataSetFunction
-
- DataVecSequencePairDataSetFunction.AlignmentMode - Enum in org.deeplearning4j.spark.datavec
-
Alignment mode for dealing with input/labels of differing lengths (for example, one-to-many and many-to-one type situations).
- datavecUris - Variable in class org.deeplearning4j.BasePipeline
-
- datavecUris() - Method in class org.deeplearning4j.BasePipeline
-
- datavecUris() - Method in interface org.deeplearning4j.Pipeline
-
The datavec uris to use
- datavecUris() - Method in class org.deeplearning4j.StreamingPipeline
-
- DATDictionary - Class in org.ansj.library
-
- DATDictionary() - Constructor for class org.ansj.library.DATDictionary
-
- DBOW<T extends SequenceElement> - Class in org.deeplearning4j.models.embeddings.learning.impl.sequence
-
- DBOW() - Constructor for class org.deeplearning4j.models.embeddings.learning.impl.sequence.DBOW
-
- dbow(int, Sequence<T>, int, AtomicLong, double, boolean, INDArray) - Method in class org.deeplearning4j.models.embeddings.learning.impl.sequence.DBOW
-
- deallocate() - Method in class org.deeplearning4j.nn.layers.BaseCudnnHelper.CudnnContext.Deallocator
-
- debug - Variable in class org.deeplearning4j.parallelism.ParallelWrapper
-
- debugLattice(OutputStream, String) - Method in class com.atilika.kuromoji.TokenizerBase
-
Writes the Viterbi lattice for the provided text to an output stream
- debugLongerIterations - Variable in class org.deeplearning4j.spark.parameterserver.conf.SharedTrainingConfiguration
-
- debugLongerIterations - Variable in class org.deeplearning4j.spark.parameterserver.training.SharedTrainingMaster.Builder
-
- debugLongerIterations(long) - Method in class org.deeplearning4j.spark.parameterserver.training.SharedTrainingMaster.Builder
-
Deprecated.
- debugLongerIterations - Variable in class org.deeplearning4j.spark.parameterserver.training.SharedTrainingMaster
-
- debugTokenize(OutputStream, String) - Method in class com.atilika.kuromoji.TokenizerBase
-
Tokenizes the provided text and outputs the corresponding Viterbi lattice and the Viterbi path to the provided output stream
- decay - Variable in class org.deeplearning4j.nn.conf.layers.BatchNormalization.Builder
-
- decay(double) - Method in class org.deeplearning4j.nn.conf.layers.BatchNormalization.Builder
-
At test time: we can use a global estimate of the mean and variance, calculated using a moving average
of the batch means/variances.
- decay - Variable in class org.deeplearning4j.nn.conf.layers.BatchNormalization
-
- decode(byte[]) - Method in interface org.deeplearning4j.api.storage.Persistable
-
Decode the content of the given
byte array in to this persistable
- decode(ByteBuffer) - Method in interface org.deeplearning4j.api.storage.Persistable
-
- decode(InputStream) - Method in interface org.deeplearning4j.api.storage.Persistable
-
Decode from the given input stream
- decode(INDArray, LayerWorkspaceMgr) - Method in class org.deeplearning4j.nn.layers.feedforward.autoencoder.AutoEncoder
-
- decode(byte[]) - Method in class org.deeplearning4j.ui.stats.impl.java.JavaStatsInitializationReport
-
- decode(ByteBuffer) - Method in class org.deeplearning4j.ui.stats.impl.java.JavaStatsInitializationReport
-
- decode(InputStream) - Method in class org.deeplearning4j.ui.stats.impl.java.JavaStatsInitializationReport
-
- decode(byte[]) - Method in class org.deeplearning4j.ui.stats.impl.java.JavaStatsReport
-
- decode(ByteBuffer) - Method in class org.deeplearning4j.ui.stats.impl.java.JavaStatsReport
-
- decode(InputStream) - Method in class org.deeplearning4j.ui.stats.impl.java.JavaStatsReport
-
- decode(byte[]) - Method in class org.deeplearning4j.ui.stats.impl.SbeStatsInitializationReport
-
- decode(ByteBuffer) - Method in class org.deeplearning4j.ui.stats.impl.SbeStatsInitializationReport
-
- decode(DirectBuffer) - Method in class org.deeplearning4j.ui.stats.impl.SbeStatsInitializationReport
-
- decode(InputStream) - Method in class org.deeplearning4j.ui.stats.impl.SbeStatsInitializationReport
-
- decode(byte[]) - Method in class org.deeplearning4j.ui.stats.impl.SbeStatsReport
-
- decode(ByteBuffer) - Method in class org.deeplearning4j.ui.stats.impl.SbeStatsReport
-
- decode(DirectBuffer) - Method in class org.deeplearning4j.ui.stats.impl.SbeStatsReport
-
- decode(InputStream) - Method in class org.deeplearning4j.ui.stats.impl.SbeStatsReport
-
- decode(DirectBuffer) - Method in interface org.deeplearning4j.ui.storage.AgronaPersistable
-
- decode(byte[]) - Method in class org.deeplearning4j.ui.storage.impl.JavaStorageMetaData
-
- decode(ByteBuffer) - Method in class org.deeplearning4j.ui.storage.impl.JavaStorageMetaData
-
- decode(InputStream) - Method in class org.deeplearning4j.ui.storage.impl.JavaStorageMetaData
-
- decode(byte[]) - Method in class org.deeplearning4j.ui.storage.impl.SbeStorageMetaData
-
- decode(ByteBuffer) - Method in class org.deeplearning4j.ui.storage.impl.SbeStorageMetaData
-
- decode(DirectBuffer) - Method in class org.deeplearning4j.ui.storage.impl.SbeStorageMetaData
-
- decode(InputStream) - Method in class org.deeplearning4j.ui.storage.impl.SbeStorageMetaData
-
- decode(byte[]) - Method in class org.deeplearning4j.ui.weights.ConvolutionListenerPersistable
-
- decode(ByteBuffer) - Method in class org.deeplearning4j.ui.weights.ConvolutionListenerPersistable
-
- decode(InputStream) - Method in class org.deeplearning4j.ui.weights.ConvolutionListenerPersistable
-
- decodeB64(String) - Static method in class org.deeplearning4j.models.embeddings.loader.WordVectorSerializer
-
- decodePredictions(INDArray, int) - Method in class org.deeplearning4j.zoo.util.BaseLabels
-
- decodePredictions(INDArray) - Method in class org.deeplearning4j.zoo.util.imagenet.ImageNetLabels
-
Given predictions from the trained model this method will return a string
listing the top five matches and the respective probabilities
- decodePredictions(INDArray, int) - Method in interface org.deeplearning4j.zoo.util.Labels
-
Given predictions from the trained model this method will return a list
of the top n matches and the respective probabilities.
- DECODER_PREFIX - Static variable in class org.deeplearning4j.nn.params.VariationalAutoencoderParamInitializer
-
- decoderLayerSizes(int...) - Method in class org.deeplearning4j.nn.conf.layers.variational.VariationalAutoencoder.Builder
-
Size of the decoder layers, in units.
- decoderLayerSizes - Variable in class org.deeplearning4j.nn.layers.variational.VariationalAutoencoder
-
- decodeUpdates(INDArray) - Method in class org.deeplearning4j.optimize.solvers.accumulation.EncodingHandler
-
Deprecated.
- Deconvolution2D - Class in org.deeplearning4j.nn.conf.layers
-
2D deconvolution layer configuration
Deconvolutions are also known as transpose convolutions or fractionally strided convolutions.
- Deconvolution2D(ConvolutionLayer.BaseConvBuilder<?>) - Constructor for class org.deeplearning4j.nn.conf.layers.Deconvolution2D
-
Deconvolution2D layer
nIn in the input layer is the number of channels
nOut is the number of filters to be used in the net or in other words the channels
The builder specifies the filter/kernel size, the stride and padding
The pooling layer takes the kernel size
- Deconvolution2D.Builder - Class in org.deeplearning4j.nn.conf.layers
-
- Deconvolution2DLayer - Class in org.deeplearning4j.nn.layers.convolution
-
2D deconvolution layer implementation.
- Deconvolution2DLayer(NeuralNetConfiguration) - Constructor for class org.deeplearning4j.nn.layers.convolution.Deconvolution2DLayer
-
- Deconvolution2DLayer(NeuralNetConfiguration, INDArray) - Constructor for class org.deeplearning4j.nn.layers.convolution.Deconvolution2DLayer
-
- DeconvolutionParamInitializer - Class in org.deeplearning4j.nn.params
-
- DeconvolutionParamInitializer() - Constructor for class org.deeplearning4j.nn.params.DeconvolutionParamInitializer
-
- DecoratorAccordion - Class in org.deeplearning4j.ui.components.decorator
-
Accordion decorator component: i.e., create an accordion (i.e., collapseable componenet) with multiple sub-components internally
Current implementation supports only one accordion section
- DecoratorAccordion() - Constructor for class org.deeplearning4j.ui.components.decorator.DecoratorAccordion
-
- DecoratorAccordion.Builder - Class in org.deeplearning4j.ui.components.decorator
-
- DeepLearningException - Exception in org.deeplearning4j.exception
-
- DeepLearningException() - Constructor for exception org.deeplearning4j.exception.DeepLearningException
-
- DeepLearningException(String, Throwable, boolean, boolean) - Constructor for exception org.deeplearning4j.exception.DeepLearningException
-
- DeepLearningException(String, Throwable) - Constructor for exception org.deeplearning4j.exception.DeepLearningException
-
- DeepLearningException(String) - Constructor for exception org.deeplearning4j.exception.DeepLearningException
-
- DeepLearningException(Throwable) - Constructor for exception org.deeplearning4j.exception.DeepLearningException
-
- DeepWalk<V,E> - Class in org.deeplearning4j.graph.models.deepwalk
-
Implementation of the DeepWalk graph vectorization model, based on the paper
DeepWalk: Online Learning of Social Representations by Perozzi, Al-Rfou & Skiena (2014),
http://arxiv.org/abs/1403.6652
Similar to word2vec in nature, DeepWalk is an unsupervised learning algorithm that learns a vector representation
of each vertex in a graph.
- DeepWalk() - Constructor for class org.deeplearning4j.graph.models.deepwalk.DeepWalk
-
- DeepWalk.Builder<V,E> - Class in org.deeplearning4j.graph.models.deepwalk
-
- DEFAULT - Static variable in class org.ansj.library.AmbiguityLibrary
-
- DEFAULT - Static variable in class org.ansj.library.CrfLibrary
-
- DEFAULT - Static variable in class org.ansj.library.DicLibrary
-
- DEFAULT - Static variable in class org.ansj.library.StopLibrary
-
- DEFAULT - Static variable in class org.ansj.library.SynonymsLibrary
-
- DEFAULT_ALPHA - Static variable in class org.deeplearning4j.nn.conf.dropout.AlphaDropout
-
- DEFAULT_AMI - Static variable in class org.deeplearning4j.aws.ec2.Ec2BoxCreator
-
- DEFAULT_BASE_RETR_DELAY_MS - Static variable in class org.deeplearning4j.api.storage.impl.RemoteUIStatsStorageRouter
-
Base delay for retries
- DEFAULT_BATCH_LIMIT - Static variable in class org.deeplearning4j.parallelism.ParallelInference
-
- DEFAULT_CHART_MARGIN_BOTTOM - Static variable in class org.deeplearning4j.ui.components.chart.style.StyleChart
-
- DEFAULT_CHART_MARGIN_LEFT - Static variable in class org.deeplearning4j.ui.components.chart.style.StyleChart
-
- DEFAULT_CHART_MARGIN_RIGHT - Static variable in class org.deeplearning4j.ui.components.chart.style.StyleChart
-
- DEFAULT_CHART_MARGIN_TOP - Static variable in class org.deeplearning4j.ui.components.chart.style.StyleChart
-
- DEFAULT_DELIMITER - Static variable in class org.deeplearning4j.spark.api.stats.CommonSparkTrainingStats
-
- DEFAULT_DELIMITER - Static variable in class org.deeplearning4j.spark.impl.paramavg.stats.ParameterAveragingTrainingMasterStats
-
- DEFAULT_DELIMITER - Static variable in class org.deeplearning4j.spark.impl.paramavg.stats.ParameterAveragingTrainingWorkerStats
-
- DEFAULT_EDGE_VALUE - Static variable in class org.deeplearning4j.eval.Evaluation
-
- DEFAULT_EDGE_VALUE - Static variable in class org.deeplearning4j.eval.EvaluationBinary
-
- DEFAULT_EPS - Static variable in class org.deeplearning4j.nn.conf.graph.L2NormalizeVertex
-
- DEFAULT_EPSILON - Static variable in class org.deeplearning4j.nn.conf.constraint.BaseConstraint
-
- DEFAULT_EVAL_SCORE_BATCH_SIZE - Static variable in class org.deeplearning4j.spark.impl.graph.SparkComputationGraph
-
- DEFAULT_EVAL_SCORE_BATCH_SIZE - Static variable in class org.deeplearning4j.spark.impl.multilayer.SparkDl4jMultiLayer
-
- DEFAULT_FLATTENING_ORDER - Static variable in class org.deeplearning4j.nn.gradient.DefaultGradient
-
- DEFAULT_FORMAT_PREC - Static variable in class org.deeplearning4j.eval.curves.BaseCurve
-
- DEFAULT_FREQ - Static variable in class org.ansj.library.DicLibrary
-
- DEFAULT_FREQ_STR - Static variable in class org.ansj.library.DicLibrary
-
- DEFAULT_HISTOGRAM_NUM_BINS - Static variable in class org.deeplearning4j.eval.EvaluationCalibration
-
- DEFAULT_INFERENCE_MODE - Static variable in class org.deeplearning4j.parallelism.ParallelInference
-
- DEFAULT_LAMBDA - Static variable in class org.deeplearning4j.nn.conf.dropout.AlphaDropout
-
- DEFAULT_LANGUAGE - Static variable in class org.deeplearning4j.ui.i18n.DefaultI18N
-
- DEFAULT_MAX_CHART_POINTS - Static variable in class org.deeplearning4j.ui.module.train.TrainModule
-
- DEFAULT_MAX_RETRIES - Static variable in class org.deeplearning4j.api.storage.impl.RemoteUIStatsStorageRouter
-
Default maximum number of (consecutive) retries on failure
- DEFAULT_MAX_TIMELINE_SIZE_MS - Static variable in class org.deeplearning4j.spark.stats.StatsUtils
-
- DEFAULT_NATURE - Static variable in class org.ansj.library.DicLibrary
-
- DEFAULT_NTP_SERVER - Static variable in class org.deeplearning4j.spark.time.NTPTimeSource
-
- DEFAULT_NTP_TIMEOUT_MS - Static variable in class org.deeplearning4j.spark.time.NTPTimeSource
-
- DEFAULT_NUM_WORKERS - Static variable in class org.deeplearning4j.parallelism.ParallelInference
-
- DEFAULT_PATH - Static variable in class org.deeplearning4j.api.storage.impl.RemoteUIStatsStorageRouter
-
Default path for posting data to the UI - i.e., http://localhost:9000/remoteReceive or similar
- DEFAULT_PATTERN - Static variable in class org.deeplearning4j.datasets.iterator.parallel.FileSplitParallelDataSetIterator
-
- DEFAULT_PRECISION - Static variable in class org.deeplearning4j.eval.EvaluationBinary
-
- DEFAULT_PRECISION - Static variable in class org.deeplearning4j.eval.RegressionEvaluation
-
- DEFAULT_PRINT_FORMAT - Static variable in interface org.deeplearning4j.spark.api.stats.SparkTrainingStats
-
- DEFAULT_PRIOR_BOXES - Static variable in class org.deeplearning4j.zoo.model.YOLO2
-
Default prior boxes for the model
- DEFAULT_QUEUE_LIMIT - Static variable in class org.deeplearning4j.parallelism.ParallelInference
-
- DEFAULT_RATE - Static variable in class org.deeplearning4j.nn.conf.constraint.MinMaxNormConstraint
-
- DEFAULT_RELIABILITY_DIAG_NUM_BINS - Static variable in class org.deeplearning4j.eval.EvaluationCalibration
-
- DEFAULT_REPORTING_FREQUENCY - Static variable in class org.deeplearning4j.ui.stats.impl.DefaultStatsUpdateConfiguration
-
- DEFAULT_RESHAPE_ORDER - Static variable in class org.deeplearning4j.nn.conf.graph.ReshapeVertex
-
- DEFAULT_RETRY_BACKOFF_FACTOR - Static variable in class org.deeplearning4j.api.storage.impl.RemoteUIStatsStorageRouter
-
Default backoff multiplicative factor for retrying
- DEFAULT_ROC_THRESHOLD_STEPS - Static variable in class org.deeplearning4j.spark.impl.graph.SparkComputationGraph
-
- DEFAULT_ROC_THRESHOLD_STEPS - Static variable in class org.deeplearning4j.spark.impl.multilayer.SparkDl4jMultiLayer
-
- DEFAULT_STATS_PRECISION - Static variable in class org.deeplearning4j.eval.ROCBinary
-
- DEFAULT_STATS_PRECISION - Static variable in class org.deeplearning4j.eval.ROCMultiClass
-
- DEFAULT_TIMESOURCE_CLASS_NAME - Static variable in class org.deeplearning4j.spark.time.TimeSourceProvider
-
Default class to use when getting a TimeSource instance
- DEFAULT_UI_PORT - Static variable in class org.deeplearning4j.ui.play.PlayUIServer
-
- DEFAULT_UNK - Static variable in class org.deeplearning4j.models.embeddings.wordvectors.WordVectorsImpl
-
- DEFAULT_UPDATE_FREQUENCY - Static variable in class org.deeplearning4j.spark.time.NTPTimeSource
-
- DEFAULT_WEIGHT_INIT_ORDER - Static variable in class org.deeplearning4j.nn.weights.WeightInitUtil
-
Default order for the arrays created by WeightInitUtil.
- defaultAnalysisEngine() - Static method in class org.deeplearning4j.text.tokenization.tokenizer.PosUimaTokenizer
-
- defaultAnalysisEngine() - Static method in class org.deeplearning4j.text.tokenization.tokenizerfactory.PosUimaTokenizerFactory
-
- defaultAnalysisEngine() - Static method in class org.deeplearning4j.text.tokenization.tokenizerfactory.UimaTokenizerFactory
-
Creates a tokenization,/stemming pipeline
- DefaultCallback - Class in org.deeplearning4j.datasets.iterator.callbacks
-
This callback ensures that memory on device is up-to-date with host memory.
- DefaultCallback() - Constructor for class org.deeplearning4j.datasets.iterator.callbacks.DefaultCallback
-
- defaultConfiguration - Variable in class org.deeplearning4j.nn.conf.ComputationGraphConfiguration
-
- defaultConfiguration - Variable in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
-
- defaultDeserializer - Variable in class org.deeplearning4j.nn.conf.serde.BaseNetConfigDeserializer
-
- DefaultGradient - Class in org.deeplearning4j.nn.gradient
-
Default gradient implementation.
- DefaultGradient() - Constructor for class org.deeplearning4j.nn.gradient.DefaultGradient
-
- DefaultGradient(INDArray) - Constructor for class org.deeplearning4j.nn.gradient.DefaultGradient
-
- DefaultI18N - Class in org.deeplearning4j.ui.i18n
-
Default internationalization implementation.
Content for internationalization is implemented using resource files.
For the resource files: they should be specified as follows:
1.
- defaultIncludeInPlots(String) - Method in class org.deeplearning4j.spark.api.stats.CommonSparkTrainingStats
-
- defaultIncludeInPlots(String) - Method in interface org.deeplearning4j.spark.api.stats.SparkTrainingStats
-
When plotting statistics, we don't necessarily want to plot everything.
- defaultIncludeInPlots(String) - Method in class org.deeplearning4j.spark.impl.paramavg.stats.ParameterAveragingTrainingMasterStats
-
- defaultIncludeInPlots(String) - Method in class org.deeplearning4j.spark.impl.paramavg.stats.ParameterAveragingTrainingWorkerStats
-
- DefaultInputStreamCreator - Class in org.deeplearning4j.bagofwords.vectorizer
-
Created by agibsonccc on 10/20/14.
- DefaultInputStreamCreator(DocumentIterator) - Constructor for class org.deeplearning4j.bagofwords.vectorizer.DefaultInputStreamCreator
-
- defaultIterationCount - Static variable in class org.deeplearning4j.clustering.strategy.OptimisationStrategy
-
- DefaultModule - Class in org.deeplearning4j.ui.module.defaultModule
-
Landing page - i.e., "/" route
- DefaultModule() - Constructor for class org.deeplearning4j.ui.module.defaultModule.DefaultModule
-
- defaultNoWorkspace() - Method in class org.deeplearning4j.nn.workspace.LayerWorkspaceMgr.Builder
-
Set the default to be scoped out for all array types.
- DefaultParamInitializer - Class in org.deeplearning4j.nn.params
-
Static weight initializer with just a weight matrix and a bias
- DefaultParamInitializer() - Constructor for class org.deeplearning4j.nn.params.DefaultParamInitializer
-
- DefaultStatsInitializationConfiguration - Class in org.deeplearning4j.ui.stats.impl
-
Created by Alex on 07/10/2016.
- DefaultStatsInitializationConfiguration() - Constructor for class org.deeplearning4j.ui.stats.impl.DefaultStatsInitializationConfiguration
-
- DefaultStatsUpdateConfiguration - Class in org.deeplearning4j.ui.stats.impl
-
Created by Alex on 07/10/2016.
- DefaultStatsUpdateConfiguration.Builder - Class in org.deeplearning4j.ui.stats.impl
-
- DefaultStepFunction - Class in org.deeplearning4j.nn.conf.stepfunctions
-
Default step function
- DefaultStepFunction() - Constructor for class org.deeplearning4j.nn.conf.stepfunctions.DefaultStepFunction
-
- DefaultStepFunction - Class in org.deeplearning4j.optimize.stepfunctions
-
Default step function
- DefaultStepFunction() - Constructor for class org.deeplearning4j.optimize.stepfunctions.DefaultStepFunction
-
- DefaultStreamTokenizer - Class in org.deeplearning4j.text.tokenization.tokenizer
-
- DefaultStreamTokenizer(InputStream) - Constructor for class org.deeplearning4j.text.tokenization.tokenizer.DefaultStreamTokenizer
-
- DefaultTokenizer - Class in org.deeplearning4j.text.tokenization.tokenizer
-
Default tokenizer
- DefaultTokenizer(String) - Constructor for class org.deeplearning4j.text.tokenization.tokenizer.DefaultTokenizer
-
- DefaultTokenizerFactory - Class in org.deeplearning4j.text.tokenization.tokenizerfactory
-
Default tokenizer based on string tokenizer or stream tokenizer
- DefaultTokenizerFactory() - Constructor for class org.deeplearning4j.text.tokenization.tokenizerfactory.DefaultTokenizerFactory
-
- DefaultTrainer - Class in org.deeplearning4j.parallelism.trainer
-
Trains datasets using a standard in memory
parameter averaging technique.
- DefaultTrainer() - Constructor for class org.deeplearning4j.parallelism.trainer.DefaultTrainer
-
- DefaultTrainer.DefaultTrainerBuilder - Class in org.deeplearning4j.parallelism.trainer
-
- DefaultTrainerBuilder() - Constructor for class org.deeplearning4j.parallelism.trainer.DefaultTrainer.DefaultTrainerBuilder
-
- DefaultTrainerContext - Class in org.deeplearning4j.parallelism.factory
-
- DefaultTrainerContext() - Constructor for class org.deeplearning4j.parallelism.factory.DefaultTrainerContext
-
- defaultVals - Static variable in class org.deeplearning4j.spark.models.embeddings.word2vec.Word2VecVariables
-
Deprecated.
- defaultWorkspace(String, WorkspaceConfiguration) - Method in class org.deeplearning4j.nn.workspace.LayerWorkspaceMgr.Builder
-
Set the default workspace for all array types to the specified workspace name/configuration
NOTE: This will NOT override any settings previously set.
- defineLayer(SameDiff, SDVariable, Map<String, SDVariable>) - Method in class org.deeplearning4j.nn.conf.layers.samediff.BaseSameDiffLayer
-
- defineParameters(SDLayerParams) - Method in class org.deeplearning4j.nn.conf.layers.samediff.AbstractSameDiffLayer
-
Define the parameters for the network.
- delete(String, String) - Static method in class org.ansj.library.DicLibrary
-
删除关键词
- delete(INDArray) - Method in class org.deeplearning4j.clustering.kdtree.KDTree
-
- deleteInvalidDataSets(JavaSparkContext, String) - Static method in class org.deeplearning4j.spark.util.data.SparkDataValidation
-
Validate DataSet objects - and delete any invalid DataSets - that have been previously saved to the
specified directory on HDFS by attempting to load them and checking their contents.
- deleteInvalidDataSets(JavaSparkContext, String, int[], int[]) - Static method in class org.deeplearning4j.spark.util.data.SparkDataValidation
-
Validate DataSet objects - and delete any invalid DataSets - that have been previously saved to the
specified directory on HDFS by attempting to load them and checking their contents.
- deleteInvalidMultiDataSets(JavaSparkContext, String) - Static method in class org.deeplearning4j.spark.util.data.SparkDataValidation
-
Validate MultiDataSet objects - and delete any invalid MultiDataSets - that have been previously saved to the
specified directory on HDFS by attempting to load them and checking their contents.
- deleteInvalidMultiDataSets(JavaSparkContext, String, List<int[]>, List<int[]>) - Static method in class org.deeplearning4j.spark.util.data.SparkDataValidation
-
Validate MultiDataSet objects - and delete any invalid MultiDataSets - that have been previously saved
to the specified directory on HDFS by attempting to load them and checking their contents.
- deleteInvalidMultiDataSets(JavaSparkContext, String, int, int) - Static method in class org.deeplearning4j.spark.util.data.SparkDataValidation
-
Validate MultiDataSet objects - and delete any invalid MultiDataSets - that have been previously saved
to the specified directory on HDFS by attempting to load them and checking their contents.
- deleteTempDir(JavaSparkContext, String) - Method in class org.deeplearning4j.spark.impl.paramavg.BaseTrainingMaster
-
- deleteTempFiles(JavaSparkContext) - Method in interface org.deeplearning4j.spark.api.TrainingMaster
-
Attempt to delete any temporary files generated by this TrainingMaster.
- deleteTempFiles(SparkContext) - Method in interface org.deeplearning4j.spark.api.TrainingMaster
-
Attempt to delete any temporary files generated by this TrainingMaster.
- deleteTempFiles(JavaSparkContext) - Method in class org.deeplearning4j.spark.impl.paramavg.BaseTrainingMaster
-
- deleteTempFiles(SparkContext) - Method in class org.deeplearning4j.spark.impl.paramavg.BaseTrainingMaster
-
- DelimitedEdgeLineProcessor - Class in org.deeplearning4j.graph.data.impl
-
A simple line processor, for data in the format
01\n 30\n etc.
- DelimitedEdgeLineProcessor(String, boolean) - Constructor for class org.deeplearning4j.graph.data.impl.DelimitedEdgeLineProcessor
-
- DelimitedEdgeLineProcessor(String, boolean, String...) - Constructor for class org.deeplearning4j.graph.data.impl.DelimitedEdgeLineProcessor
-
- DelimitedVertexLoader - Class in org.deeplearning4j.graph.data.impl
-
Load vertex information, one per line of form "0Some text attribute/label"
- DelimitedVertexLoader(String) - Constructor for class org.deeplearning4j.graph.data.impl.DelimitedVertexLoader
-
- DelimitedVertexLoader(String, String...) - Constructor for class org.deeplearning4j.graph.data.impl.DelimitedVertexLoader
-
- deltaGCCount() - Method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder.GcStatsDecoder
-
- deltaGCCount(int) - Method in class org.deeplearning4j.ui.stats.sbe.UpdateEncoder.GcStatsEncoder
-
- deltaGCCountId() - Static method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder.GcStatsDecoder
-
- deltaGCCountMaxValue() - Static method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder.GcStatsDecoder
-
- deltaGCCountMaxValue() - Static method in class org.deeplearning4j.ui.stats.sbe.UpdateEncoder.GcStatsEncoder
-
- deltaGCCountMetaAttribute(MetaAttribute) - Static method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder.GcStatsDecoder
-
- deltaGCCountMinValue() - Static method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder.GcStatsDecoder
-
- deltaGCCountMinValue() - Static method in class org.deeplearning4j.ui.stats.sbe.UpdateEncoder.GcStatsEncoder
-
- deltaGCCountNullValue() - Static method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder.GcStatsDecoder
-
- deltaGCCountNullValue() - Static method in class org.deeplearning4j.ui.stats.sbe.UpdateEncoder.GcStatsEncoder
-
- deltaGCTimeMs() - Method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder.GcStatsDecoder
-
- deltaGCTimeMs(int) - Method in class org.deeplearning4j.ui.stats.sbe.UpdateEncoder.GcStatsEncoder
-
- deltaGCTimeMsId() - Static method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder.GcStatsDecoder
-
- deltaGCTimeMsMaxValue() - Static method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder.GcStatsDecoder
-
- deltaGCTimeMsMaxValue() - Static method in class org.deeplearning4j.ui.stats.sbe.UpdateEncoder.GcStatsEncoder
-
- deltaGCTimeMsMetaAttribute(MetaAttribute) - Static method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder.GcStatsDecoder
-
- deltaGCTimeMsMinValue() - Static method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder.GcStatsDecoder
-
- deltaGCTimeMsMinValue() - Static method in class org.deeplearning4j.ui.stats.sbe.UpdateEncoder.GcStatsEncoder
-
- deltaGCTimeMsNullValue() - Static method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder.GcStatsDecoder
-
- deltaGCTimeMsNullValue() - Static method in class org.deeplearning4j.ui.stats.sbe.UpdateEncoder.GcStatsEncoder
-
- deltaTime() - Method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder
-
- deltaTime(int) - Method in class org.deeplearning4j.ui.stats.sbe.UpdateEncoder
-
- deltaTimeId() - Static method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder
-
- deltaTimeMaxValue() - Static method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder
-
- deltaTimeMaxValue() - Static method in class org.deeplearning4j.ui.stats.sbe.UpdateEncoder
-
- deltaTimeMetaAttribute(MetaAttribute) - Static method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder
-
- deltaTimeMinValue() - Static method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder
-
- deltaTimeMinValue() - Static method in class org.deeplearning4j.ui.stats.sbe.UpdateEncoder
-
- deltaTimeNullValue() - Static method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder
-
- deltaTimeNullValue() - Static method in class org.deeplearning4j.ui.stats.sbe.UpdateEncoder
-
- denseCounter - Variable in class org.deeplearning4j.spark.parameterserver.networking.SilentTrainingDriver
-
- DenseLayer - Class in org.deeplearning4j.nn.conf.layers
-
Dense layer: fully connected feed forward layer trainable by backprop.
- DenseLayer - Class in org.deeplearning4j.nn.layers.feedforward.dense
-
- DenseLayer(NeuralNetConfiguration) - Constructor for class org.deeplearning4j.nn.layers.feedforward.dense.DenseLayer
-
- DenseLayer(NeuralNetConfiguration, INDArray) - Constructor for class org.deeplearning4j.nn.layers.feedforward.dense.DenseLayer
-
- DenseLayer.Builder - Class in org.deeplearning4j.nn.conf.layers
-
- depth() - Method in class org.deeplearning4j.clustering.quadtree.QuadTree
-
The depth of the node
- depth() - Method in class org.deeplearning4j.clustering.sptree.SpTree
-
The depth of the node
- depth - Variable in class org.deeplearning4j.models.sequencevectors.graph.walkers.impl.NearestVertexWalker.Builder
-
- depth - Variable in class org.deeplearning4j.models.sequencevectors.graph.walkers.impl.NearestVertexWalker
-
- depth() - Method in class org.deeplearning4j.nn.layers.feedforward.autoencoder.recursive.Tree
-
Finds the channels of the tree.
- depth(Tree) - Method in class org.deeplearning4j.nn.layers.feedforward.autoencoder.recursive.Tree
-
Returns the distance between this node
and the specified subnode
- DEPTH_WISE_WEIGHT_KEY - Static variable in class org.deeplearning4j.nn.params.SeparableConvolutionParamInitializer
-
- depthMultiplier - Variable in class org.deeplearning4j.nn.conf.layers.DepthwiseConvolution2D.Builder
-
- depthMultiplier(int) - Method in class org.deeplearning4j.nn.conf.layers.DepthwiseConvolution2D.Builder
-
Set channels multiplier for depth-wise convolution
- depthMultiplier - Variable in class org.deeplearning4j.nn.conf.layers.SeparableConvolution2D.Builder
-
- depthMultiplier(int) - Method in class org.deeplearning4j.nn.conf.layers.SeparableConvolution2D.Builder
-
Set channels multiplier of channels-wise step in separable convolution
- DepthwiseConvolution2D - Class in org.deeplearning4j.nn.conf.layers
-
2D depth-wise convolution layer configuration.
- DepthwiseConvolution2D(DepthwiseConvolution2D.Builder) - Constructor for class org.deeplearning4j.nn.conf.layers.DepthwiseConvolution2D
-
- DepthwiseConvolution2D.Builder - Class in org.deeplearning4j.nn.conf.layers
-
- DepthwiseConvolution2DLayer - Class in org.deeplearning4j.nn.layers.convolution
-
2D depth-wise convolution layer configuration.
- DepthwiseConvolution2DLayer(NeuralNetConfiguration) - Constructor for class org.deeplearning4j.nn.layers.convolution.DepthwiseConvolution2DLayer
-
- DepthwiseConvolution2DLayer(NeuralNetConfiguration, INDArray) - Constructor for class org.deeplearning4j.nn.layers.convolution.DepthwiseConvolution2DLayer
-
- DepthwiseConvolutionParamInitializer - Class in org.deeplearning4j.nn.params
-
Initialize depth-wise convolution parameters.
- DepthwiseConvolutionParamInitializer() - Constructor for class org.deeplearning4j.nn.params.DepthwiseConvolutionParamInitializer
-
- deregisterStatsStorageListener(StatsStorageListener) - Method in interface org.deeplearning4j.api.storage.StatsStorage
-
Remove the specified listener, if it is present.
- deregisterStatsStorageListener(StatsStorageListener) - Method in class org.deeplearning4j.ui.storage.BaseCollectionStatsStorage
-
- deregisterStatsStorageListener(StatsStorageListener) - Method in class org.deeplearning4j.ui.storage.sqlite.J7FileStatsStorage
-
- deriveClusterInfoDistanceStatistics(ClusterInfo) - Static method in class org.deeplearning4j.clustering.cluster.ClusterUtils
-
- deserialize(JsonParser, DeserializationContext) - Method in class org.deeplearning4j.eval.serde.ConfusionMatrixDeserializer
-
- deserialize(String) - Method in interface org.deeplearning4j.models.sequencevectors.interfaces.SequenceElementFactory
-
This method builds object from provided JSON
- deserialize(String) - Method in class org.deeplearning4j.models.sequencevectors.serialization.AbstractElementFactory
-
This method builds object from provided JSON
- deserialize(String) - Method in class org.deeplearning4j.models.sequencevectors.serialization.VocabWordFactory
-
This method builds object from provided JSON
- deserialize(JsonParser, DeserializationContext) - Method in class org.deeplearning4j.nn.conf.distribution.serde.LegacyDistributionDeserializer
-
- deserialize(JsonParser, DeserializationContext) - Method in class org.deeplearning4j.nn.conf.serde.BaseNetConfigDeserializer
-
- deserialize(JsonParser, DeserializationContext) - Method in class org.deeplearning4j.nn.conf.serde.ComputationGraphConfigurationDeserializer
-
- deserialize(JsonParser, DeserializationContext) - Method in class org.deeplearning4j.nn.conf.serde.legacyformat.LegacyIntArrayDeserializer
-
- deserialize(JsonParser, DeserializationContext) - Method in class org.deeplearning4j.nn.conf.serde.MultiLayerConfigurationDeserializer
-
- deserialize(JsonParser, DeserializationContext) - Method in class org.deeplearning4j.spark.util.serde.StorageLevelDeserializer
-
- destroy() - Method in class org.deeplearning4j.text.annotator.PoStagger
-
Releases allocated resources.
- destroy() - Method in class org.deeplearning4j.text.tokenization.tokenizer.ConcurrentTokenizer
-
Releases allocated resources.
- destroyHandles() - Method in class org.deeplearning4j.nn.layers.BaseCudnnHelper.CudnnContext
-
- detach(StatsStorage) - Method in class org.deeplearning4j.ui.api.UIServer
-
Detach the specified StatsStorage instance from the UI
- detach(StatsStorage) - Method in class org.deeplearning4j.ui.play.PlayUIServer
-
- DetectedObject - Class in org.deeplearning4j.nn.layers.objdetect
-
A detected object, by an object detection algorithm.
- DetectedObject(int, double, double, double, double, INDArray, double) - Constructor for class org.deeplearning4j.nn.layers.objdetect.DetectedObject
-
- determinationCoefficient(double[], double[], int) - Static method in class org.deeplearning4j.clustering.util.MathUtils
-
This returns the determination coefficient of two vectors given a length
- determineKerasBackend(Map<String, Object>, KerasModelConfiguration) - Static method in class org.deeplearning4j.nn.modelimport.keras.utils.KerasModelUtils
-
Determine Keras backend
- determineKerasMajorVersion(Map<String, Object>, KerasModelConfiguration) - Static method in class org.deeplearning4j.nn.modelimport.keras.utils.KerasModelUtils
-
Determine Keras major version
- deviceDescription() - Method in class org.deeplearning4j.ui.stats.sbe.StaticInfoDecoder.HwDeviceInfoGroupDecoder
-
- deviceDescription(String) - Method in class org.deeplearning4j.ui.stats.sbe.StaticInfoEncoder.HwDeviceInfoGroupEncoder
-
- deviceDescriptionCharacterEncoding() - Static method in class org.deeplearning4j.ui.stats.sbe.StaticInfoDecoder.HwDeviceInfoGroupDecoder
-
- deviceDescriptionCharacterEncoding() - Static method in class org.deeplearning4j.ui.stats.sbe.StaticInfoEncoder.HwDeviceInfoGroupEncoder
-
- deviceDescriptionHeaderLength() - Static method in class org.deeplearning4j.ui.stats.sbe.StaticInfoDecoder.HwDeviceInfoGroupDecoder
-
- deviceDescriptionHeaderLength() - Static method in class org.deeplearning4j.ui.stats.sbe.StaticInfoEncoder.HwDeviceInfoGroupEncoder
-
- deviceDescriptionId() - Static method in class org.deeplearning4j.ui.stats.sbe.StaticInfoDecoder.HwDeviceInfoGroupDecoder
-
- deviceDescriptionId() - Static method in class org.deeplearning4j.ui.stats.sbe.StaticInfoEncoder.HwDeviceInfoGroupEncoder
-
- deviceDescriptionLength() - Method in class org.deeplearning4j.ui.stats.sbe.StaticInfoDecoder.HwDeviceInfoGroupDecoder
-
- deviceDescriptionMetaAttribute(MetaAttribute) - Static method in class org.deeplearning4j.ui.stats.sbe.StaticInfoDecoder.HwDeviceInfoGroupDecoder
-
- deviceDescriptionMetaAttribute(MetaAttribute) - Static method in class org.deeplearning4j.ui.stats.sbe.StaticInfoEncoder.HwDeviceInfoGroupEncoder
-
- deviceId - Variable in class org.deeplearning4j.datasets.iterator.AsyncDataSetIterator
-
- deviceId - Variable in class org.deeplearning4j.datasets.iterator.AsyncMultiDataSetIterator
-
- deviceMemoryMax() - Method in class org.deeplearning4j.ui.stats.sbe.StaticInfoDecoder.HwDeviceInfoGroupDecoder
-
- deviceMemoryMax(long) - Method in class org.deeplearning4j.ui.stats.sbe.StaticInfoEncoder.HwDeviceInfoGroupEncoder
-
- deviceMemoryMaxId() - Static method in class org.deeplearning4j.ui.stats.sbe.StaticInfoDecoder.HwDeviceInfoGroupDecoder
-
- deviceMemoryMaxMaxValue() - Static method in class org.deeplearning4j.ui.stats.sbe.StaticInfoDecoder.HwDeviceInfoGroupDecoder
-
- deviceMemoryMaxMaxValue() - Static method in class org.deeplearning4j.ui.stats.sbe.StaticInfoEncoder.HwDeviceInfoGroupEncoder
-
- deviceMemoryMaxMetaAttribute(MetaAttribute) - Static method in class org.deeplearning4j.ui.stats.sbe.StaticInfoDecoder.HwDeviceInfoGroupDecoder
-
- deviceMemoryMaxMinValue() - Static method in class org.deeplearning4j.ui.stats.sbe.StaticInfoDecoder.HwDeviceInfoGroupDecoder
-
- deviceMemoryMaxMinValue() - Static method in class org.deeplearning4j.ui.stats.sbe.StaticInfoEncoder.HwDeviceInfoGroupEncoder
-
- deviceMemoryMaxNullValue() - Static method in class org.deeplearning4j.ui.stats.sbe.StaticInfoDecoder.HwDeviceInfoGroupDecoder
-
- deviceMemoryMaxNullValue() - Static method in class org.deeplearning4j.ui.stats.sbe.StaticInfoEncoder.HwDeviceInfoGroupEncoder
-
- DeviceMetric - Class in org.deeplearning4j.perf.listener
-
- diag(INDArray) - Method in class org.deeplearning4j.plot.Tsne
-
- DicAnalysis - Class in org.ansj.splitWord.analysis
-
默认用户自定义词性优先
- DicAnalysis() - Constructor for class org.ansj.splitWord.analysis.DicAnalysis
-
- DicAnalysis(Reader) - Constructor for class org.ansj.splitWord.analysis.DicAnalysis
-
- DicLibrary - Class in org.ansj.library
-
- DicLibrary() - Constructor for class org.ansj.library.DicLibrary
-
- DicReader - Class in org.ansj.dic
-
加载词典用的类
- DicReader() - Constructor for class org.ansj.dic.DicReader
-
- DicRecognition - Class in org.ansj.recognition.impl
-
用户自定词典识别 多本词典加入后将不再具有先后顺序,合并后统一规划.如果需要先后顺序请分别每个词典调用 Result.Recognition().Recognition() 这种方式 TODO:这种写灵活性是够了,但是速度不咋地.发愁........该不该这么写.先保留吧..也许在下一个版本中来做把
- DicRecognition() - Constructor for class org.ansj.recognition.impl.DicRecognition
-
- DicRecognition(String[]) - Constructor for class org.ansj.recognition.impl.DicRecognition
-
- DicRecognition(Forest[]) - Constructor for class org.ansj.recognition.impl.DicRecognition
-
- DicRecognition(Forest) - Constructor for class org.ansj.recognition.impl.DicRecognition
-
- Dictionary - Interface in com.atilika.kuromoji.dict
-
- DictionaryCompiler - Class in com.atilika.kuromoji.ipadic.compile
-
- DictionaryCompiler() - Constructor for class com.atilika.kuromoji.ipadic.compile.DictionaryCompiler
-
- DictionaryCompilerBase - Class in com.atilika.kuromoji.compile
-
- DictionaryCompilerBase() - Constructor for class com.atilika.kuromoji.compile.DictionaryCompilerBase
-
- dictionaryEntries - Variable in class com.atilika.kuromoji.compile.TokenInfoDictionaryCompilerBase
-
- dictionaryEntries - Variable in class com.atilika.kuromoji.compile.UnknownDictionaryCompiler
-
- DictionaryEntry - Class in com.atilika.kuromoji.ipadic.compile
-
- DictionaryEntry(String[]) - Constructor for class com.atilika.kuromoji.ipadic.compile.DictionaryEntry
-
- DictionaryEntryBase - Class in com.atilika.kuromoji.dict
-
- DictionaryEntryBase(String, short, short, short) - Constructor for class com.atilika.kuromoji.dict.DictionaryEntryBase
-
- DictionaryEntryLineParser - Class in com.atilika.kuromoji.util
-
- DictionaryEntryLineParser() - Constructor for class com.atilika.kuromoji.util.DictionaryEntryLineParser
-
- DictionaryField - Class in com.atilika.kuromoji.dict
-
- DictionaryField() - Constructor for class com.atilika.kuromoji.dict.DictionaryField
-
- dictionaryMap - Variable in class com.atilika.kuromoji.TokenizerBase
-
- difference(Collection<? extends T>, Collection<? extends T>) - Static method in class org.deeplearning4j.clustering.util.SetUtils
-
Return is s1 \ s2
- dilation(int...) - Method in class org.deeplearning4j.nn.conf.layers.Convolution3D.Builder
-
Set dilation size for 3D convolutions in (depth, height, width) order
- dilation - Variable in class org.deeplearning4j.nn.conf.layers.ConvolutionLayer.BaseConvBuilder
-
- dilation(int...) - Method in class org.deeplearning4j.nn.conf.layers.ConvolutionLayer.BaseConvBuilder
-
Kernel dilation.
- dilation - Variable in class org.deeplearning4j.nn.conf.layers.ConvolutionLayer
-
- dilation(int...) - Method in class org.deeplearning4j.nn.conf.layers.SubsamplingLayer.Builder
-
Kernel dilation.
- dilation - Variable in class org.deeplearning4j.nn.conf.layers.SubsamplingLayer
-
- dimension - Variable in class org.deeplearning4j.nn.conf.graph.L2NormalizeVertex
-
- dimensions - Variable in class org.deeplearning4j.nn.conf.constraint.BaseConstraint
-
- dimOrder - Variable in class org.deeplearning4j.nn.modelimport.keras.KerasLayer
-
- DIRECT_ROUTE - Static variable in class org.deeplearning4j.streaming.kafka.NDArrayConsumer
-
- DIRECT_ROUTE - Static variable in class org.deeplearning4j.streaming.kafka.NDArrayPublisher
-
- disableLogging() - Static method in class org.deeplearning4j.text.movingwindow.Util
-
- disableRemoteListener() - Method in class org.deeplearning4j.ui.api.UIServer
-
Disable the remote listener functionality (disabled by default)
- disableRemoteListener() - Method in class org.deeplearning4j.ui.play.PlayUIServer
-
- discretize(double, double, double, int) - Static method in class org.deeplearning4j.clustering.util.MathUtils
-
Discretize the given value
- DiskBasedQueue<E> - Class in org.deeplearning4j.util
-
Naive disk based queue for storing items on disk.
- DiskBasedQueue() - Constructor for class org.deeplearning4j.util.DiskBasedQueue
-
- DiskBasedQueue(String) - Constructor for class org.deeplearning4j.util.DiskBasedQueue
-
- DiskBasedQueue(File) - Constructor for class org.deeplearning4j.util.DiskBasedQueue
-
- DiskInfo - Class in org.deeplearning4j.perf.listener
-
- dist - Variable in class org.deeplearning4j.nn.conf.layers.BaseLayer.Builder
-
- dist(Distribution) - Method in class org.deeplearning4j.nn.conf.layers.BaseLayer.Builder
-
Distribution to sample initial weights from.
- dist - Variable in class org.deeplearning4j.nn.conf.layers.BaseLayer
-
- dist - Variable in class org.deeplearning4j.nn.conf.NeuralNetConfiguration.Builder
-
- dist(Distribution) - Method in class org.deeplearning4j.nn.conf.NeuralNetConfiguration.Builder
-
Distribution to sample initial weights from.
- dist(Distribution) - Method in class org.deeplearning4j.nn.transferlearning.FineTuneConfiguration.Builder
-
Distribution to sample initial weights from.
- dist - Variable in class org.deeplearning4j.nn.transferlearning.FineTuneConfiguration
-
- distance(DataPoint) - Method in class org.deeplearning4j.clustering.sptree.DataPoint
-
Euclidean distance
- distance(INDArray, INDArray) - Method in class org.deeplearning4j.clustering.vptree.VPTree
-
Euclidean distance
- distanceFinderZValue(double[]) - Static method in class org.deeplearning4j.clustering.util.MathUtils
-
This will translate a vector in to an equivalent integer
- distanceFunction - Variable in class org.deeplearning4j.clustering.strategy.BaseClusteringStrategy
-
- distRecurrent - Variable in class org.deeplearning4j.nn.conf.layers.BaseRecurrentLayer.Builder
-
- distRecurrent - Variable in class org.deeplearning4j.nn.conf.layers.BaseRecurrentLayer
-
- DistributedDeepLearningTrainer - Class in org.deeplearning4j.aws.ec2.provision
-
- DistributedFunction<T extends SequenceElement> - Class in org.deeplearning4j.spark.models.sequencevectors.functions
-
- DistributedFunction(Broadcast<VoidConfiguration>, Broadcast<VectorsConfiguration>, Broadcast<VocabCache<ShallowSequenceElement>>) - Constructor for class org.deeplearning4j.spark.models.sequencevectors.functions.DistributedFunction
-
- Distribution - Class in org.deeplearning4j.nn.conf.distribution
-
An abstract distribution.
- Distribution() - Constructor for class org.deeplearning4j.nn.conf.distribution.Distribution
-
- distributionInputSize(int) - Method in class org.deeplearning4j.nn.conf.layers.variational.BernoulliReconstructionDistribution
-
- distributionInputSize(int) - Method in class org.deeplearning4j.nn.conf.layers.variational.CompositeReconstructionDistribution
-
- distributionInputSize(int) - Method in class org.deeplearning4j.nn.conf.layers.variational.ExponentialReconstructionDistribution
-
- distributionInputSize(int) - Method in class org.deeplearning4j.nn.conf.layers.variational.GaussianReconstructionDistribution
-
- distributionInputSize(int) - Method in class org.deeplearning4j.nn.conf.layers.variational.LossFunctionWrapper
-
- distributionInputSize(int) - Method in interface org.deeplearning4j.nn.conf.layers.variational.ReconstructionDistribution
-
Get the number of distribution parameters for the given input data size.
- Distributions - Class in org.deeplearning4j.nn.conf.distribution
-
Static method for instantiating an nd4j distribution from a configuration object.
- distributionVariationRateLessThan(double) - Static method in class org.deeplearning4j.clustering.condition.ConvergenceCondition
-
- DL4J_DIR - Static variable in class org.deeplearning4j.datasets.fetchers.CacheableExtractableDataSetFetcher
-
- DL4JException - Exception in org.deeplearning4j.exception
-
Base exception for DL4J
- DL4JException() - Constructor for exception org.deeplearning4j.exception.DL4JException
-
- DL4JException(String) - Constructor for exception org.deeplearning4j.exception.DL4JException
-
- DL4JException(String, Throwable) - Constructor for exception org.deeplearning4j.exception.DL4JException
-
- DL4JException(Throwable) - Constructor for exception org.deeplearning4j.exception.DL4JException
-
- DL4JInvalidConfigException - Exception in org.deeplearning4j.exception
-
Exception signifying that the specified configuration is invalid
- DL4JInvalidConfigException() - Constructor for exception org.deeplearning4j.exception.DL4JInvalidConfigException
-
- DL4JInvalidConfigException(String) - Constructor for exception org.deeplearning4j.exception.DL4JInvalidConfigException
-
- DL4JInvalidConfigException(String, Throwable) - Constructor for exception org.deeplearning4j.exception.DL4JInvalidConfigException
-
- DL4JInvalidConfigException(Throwable) - Constructor for exception org.deeplearning4j.exception.DL4JInvalidConfigException
-
- DL4JInvalidInputException - Exception in org.deeplearning4j.exception
-
DL4J Exception thrown when invalid input is provided (wrong rank, wrong size, etc)
- DL4JInvalidInputException() - Constructor for exception org.deeplearning4j.exception.DL4JInvalidInputException
-
- DL4JInvalidInputException(String) - Constructor for exception org.deeplearning4j.exception.DL4JInvalidInputException
-
- DL4JInvalidInputException(String, Throwable) - Constructor for exception org.deeplearning4j.exception.DL4JInvalidInputException
-
- DL4JInvalidInputException(Throwable) - Constructor for exception org.deeplearning4j.exception.DL4JInvalidInputException
-
- Dl4jReflection - Class in org.deeplearning4j.util
-
- DL4jServeRouteBuilder - Class in org.deeplearning4j.streaming.routes
-
Serve results from a kafka queue.
- DL4jServeRouteBuilder() - Constructor for class org.deeplearning4j.streaming.routes.DL4jServeRouteBuilder
-
- DM<T extends SequenceElement> - Class in org.deeplearning4j.models.embeddings.learning.impl.sequence
-
DM implementation for DeepLearning4j
- DM() - Constructor for class org.deeplearning4j.models.embeddings.learning.impl.sequence.DM
-
- dm(int, Sequence<T>, int, AtomicLong, double, List<T>, boolean, INDArray) - Method in class org.deeplearning4j.models.embeddings.learning.impl.sequence.DM
-
- doBackward(boolean, LayerWorkspaceMgr) - Method in class org.deeplearning4j.nn.graph.vertex.BaseWrapperVertex
-
- doBackward(boolean, LayerWorkspaceMgr) - Method in interface org.deeplearning4j.nn.graph.vertex.GraphVertex
-
Do backward pass
- doBackward(boolean, LayerWorkspaceMgr) - Method in class org.deeplearning4j.nn.graph.vertex.impl.ElementWiseVertex
-
- doBackward(boolean, LayerWorkspaceMgr) - Method in class org.deeplearning4j.nn.graph.vertex.impl.InputVertex
-
- doBackward(boolean, LayerWorkspaceMgr) - Method in class org.deeplearning4j.nn.graph.vertex.impl.L2NormalizeVertex
-
- doBackward(boolean, LayerWorkspaceMgr) - Method in class org.deeplearning4j.nn.graph.vertex.impl.L2Vertex
-
- doBackward(boolean, LayerWorkspaceMgr) - Method in class org.deeplearning4j.nn.graph.vertex.impl.LayerVertex
-
- doBackward(boolean, LayerWorkspaceMgr) - Method in class org.deeplearning4j.nn.graph.vertex.impl.MergeVertex
-
- doBackward(boolean, LayerWorkspaceMgr) - Method in class org.deeplearning4j.nn.graph.vertex.impl.PoolHelperVertex
-
- doBackward(boolean, LayerWorkspaceMgr) - Method in class org.deeplearning4j.nn.graph.vertex.impl.PreprocessorVertex
-
- doBackward(boolean, LayerWorkspaceMgr) - Method in class org.deeplearning4j.nn.graph.vertex.impl.ReshapeVertex
-
- doBackward(boolean, LayerWorkspaceMgr) - Method in class org.deeplearning4j.nn.graph.vertex.impl.rnn.DuplicateToTimeSeriesVertex
-
- doBackward(boolean, LayerWorkspaceMgr) - Method in class org.deeplearning4j.nn.graph.vertex.impl.rnn.LastTimeStepVertex
-
- doBackward(boolean, LayerWorkspaceMgr) - Method in class org.deeplearning4j.nn.graph.vertex.impl.rnn.ReverseTimeSeriesVertex
-
- doBackward(boolean, LayerWorkspaceMgr) - Method in class org.deeplearning4j.nn.graph.vertex.impl.ScaleVertex
-
- doBackward(boolean, LayerWorkspaceMgr) - Method in class org.deeplearning4j.nn.graph.vertex.impl.ShiftVertex
-
- doBackward(boolean, LayerWorkspaceMgr) - Method in class org.deeplearning4j.nn.graph.vertex.impl.StackVertex
-
- doBackward(boolean, LayerWorkspaceMgr) - Method in class org.deeplearning4j.nn.graph.vertex.impl.SubsetVertex
-
- doBackward(boolean, LayerWorkspaceMgr) - Method in class org.deeplearning4j.nn.graph.vertex.impl.UnstackVertex
-
- docAppearedIn(String) - Method in class org.deeplearning4j.models.word2vec.wordstore.inmemory.AbstractCache
-
Returns number of documents (if applicable) the label was observed in.
- docAppearedIn(String) - Method in class org.deeplearning4j.models.word2vec.wordstore.inmemory.InMemoryLookupCache
-
Deprecated.
- docAppearedIn(String) - Method in interface org.deeplearning4j.models.word2vec.wordstore.VocabCache
-
Count of documents a word appeared in
- docFrequencies - Variable in class org.deeplearning4j.models.word2vec.wordstore.inmemory.InMemoryLookupCache
-
Deprecated.
- docIter - Variable in class org.deeplearning4j.bagofwords.vectorizer.Builder
-
Deprecated.
- docIter - Variable in class org.deeplearning4j.models.paragraphvectors.ParagraphVectors.Builder
-
- docs() - Method in interface org.deeplearning4j.text.invertedindex.InvertedIndex
-
Iterate over documents
- document(int) - Method in interface org.deeplearning4j.text.invertedindex.InvertedIndex
-
Returns a list of words for a document
- documentIterator - Variable in class org.deeplearning4j.models.glove.Glove.Builder
-
- DocumentIterator - Interface in org.deeplearning4j.text.documentiterator
-
Document Iterator: iterate over input streams
- DocumentIteratorConverter - Class in org.deeplearning4j.text.documentiterator.interoperability
-
Simple class providing compatibility between DocumentIterator/LabelAwareDocumentIterator and LabelAwareIterator
- DocumentIteratorConverter(LabelAwareDocumentIterator) - Constructor for class org.deeplearning4j.text.documentiterator.interoperability.DocumentIteratorConverter
-
- DocumentIteratorConverter(DocumentIterator, LabelsSource) - Constructor for class org.deeplearning4j.text.documentiterator.interoperability.DocumentIteratorConverter
-
- documentPosition - Variable in class org.deeplearning4j.text.documentiterator.BasicLabelAwareIterator
-
- documents(T) - Method in interface org.deeplearning4j.text.invertedindex.InvertedIndex
-
Returns the list of documents a vocab word is in
- DocumentSequenceConvertFunction - Class in org.deeplearning4j.spark.models.paragraphvectors.functions
-
- DocumentSequenceConvertFunction(Broadcast<VectorsConfiguration>) - Constructor for class org.deeplearning4j.spark.models.paragraphvectors.functions.DocumentSequenceConvertFunction
-
- documentWithLabel(int) - Method in interface org.deeplearning4j.text.invertedindex.InvertedIndex
-
Returns a list of words for a document
and the associated label
- documentWithLabels(int) - Method in interface org.deeplearning4j.text.invertedindex.InvertedIndex
-
Returns a list of words associated with the document
and the associated labels
- doEvaluation(DataSetIterator, T...) - Method in interface org.deeplearning4j.nn.api.NeuralNetwork
-
This method executes evaluation of the model against given iterator and evaluation implementations
- doEvaluation(MultiDataSetIterator, T...) - Method in interface org.deeplearning4j.nn.api.NeuralNetwork
-
This method executes evaluation of the model against given iterator and evaluation implementations
- doEvaluation(DataSetIterator, T...) - Method in class org.deeplearning4j.nn.graph.ComputationGraph
-
Perform evaluation on the given data (DataSetIterator) with the given
IEvaluation instance
- doEvaluation(MultiDataSetIterator, T...) - Method in class org.deeplearning4j.nn.graph.ComputationGraph
-
Perform evaluation on the given data (MultiDataSetIterator) with the given
IEvaluation instance
- doEvaluation(DataSetIterator, T...) - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
-
Perform evaluation using an arbitrary IEvaluation instance.
- doEvaluation(MultiDataSetIterator, T[]) - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
-
- doEvaluation(JavaRDD<DataSet>, T, int) - Method in class org.deeplearning4j.spark.impl.graph.SparkComputationGraph
-
Perform distributed evaluation of any type of
IEvaluation.
- doEvaluation(JavaRDD<DataSet>, int, T...) - Method in class org.deeplearning4j.spark.impl.graph.SparkComputationGraph
-
Perform distributed evaluation on a single output ComputationGraph form DataSet objects using Spark.
- doEvaluation(JavaRDD<DataSet>, T, int) - Method in class org.deeplearning4j.spark.impl.multilayer.SparkDl4jMultiLayer
-
Perform distributed evaluation of any type of
IEvaluation.
- doEvaluation(JavaRDD<DataSet>, int, T...) - Method in class org.deeplearning4j.spark.impl.multilayer.SparkDl4jMultiLayer
-
Perform distributed evaluation of any type of
IEvaluation - or multiple IEvaluation instances.
- doEvaluationMDS(JavaRDD<MultiDataSet>, int, T...) - Method in class org.deeplearning4j.spark.impl.graph.SparkComputationGraph
-
Perform distributed evaluation on a single output ComputationGraph form MultiDataSet objects using Spark.
- doForward(boolean, LayerWorkspaceMgr) - Method in class org.deeplearning4j.nn.graph.vertex.BaseWrapperVertex
-
- doForward(boolean, LayerWorkspaceMgr) - Method in interface org.deeplearning4j.nn.graph.vertex.GraphVertex
-
Do forward pass using the stored inputs
- doForward(boolean, LayerWorkspaceMgr) - Method in class org.deeplearning4j.nn.graph.vertex.impl.ElementWiseVertex
-
- doForward(boolean, LayerWorkspaceMgr) - Method in class org.deeplearning4j.nn.graph.vertex.impl.InputVertex
-
- doForward(boolean, LayerWorkspaceMgr) - Method in class org.deeplearning4j.nn.graph.vertex.impl.L2NormalizeVertex
-
- doForward(boolean, LayerWorkspaceMgr) - Method in class org.deeplearning4j.nn.graph.vertex.impl.L2Vertex
-
- doForward(boolean, LayerWorkspaceMgr) - Method in class org.deeplearning4j.nn.graph.vertex.impl.LayerVertex
-
- doForward(boolean, LayerWorkspaceMgr) - Method in class org.deeplearning4j.nn.graph.vertex.impl.MergeVertex
-
- doForward(boolean, LayerWorkspaceMgr) - Method in class org.deeplearning4j.nn.graph.vertex.impl.PoolHelperVertex
-
- doForward(boolean, LayerWorkspaceMgr) - Method in class org.deeplearning4j.nn.graph.vertex.impl.PreprocessorVertex
-
- doForward(boolean, LayerWorkspaceMgr) - Method in class org.deeplearning4j.nn.graph.vertex.impl.ReshapeVertex
-
- doForward(boolean, LayerWorkspaceMgr) - Method in class org.deeplearning4j.nn.graph.vertex.impl.rnn.DuplicateToTimeSeriesVertex
-
- doForward(boolean, LayerWorkspaceMgr) - Method in class org.deeplearning4j.nn.graph.vertex.impl.rnn.LastTimeStepVertex
-
- doForward(boolean, LayerWorkspaceMgr) - Method in class org.deeplearning4j.nn.graph.vertex.impl.rnn.ReverseTimeSeriesVertex
-
- doForward(boolean, LayerWorkspaceMgr) - Method in class org.deeplearning4j.nn.graph.vertex.impl.ScaleVertex
-
- doForward(boolean, LayerWorkspaceMgr) - Method in class org.deeplearning4j.nn.graph.vertex.impl.ShiftVertex
-
- doForward(boolean, LayerWorkspaceMgr) - Method in class org.deeplearning4j.nn.graph.vertex.impl.StackVertex
-
- doForward(boolean, LayerWorkspaceMgr) - Method in class org.deeplearning4j.nn.graph.vertex.impl.SubsetVertex
-
- doForward(boolean, LayerWorkspaceMgr) - Method in class org.deeplearning4j.nn.graph.vertex.impl.UnstackVertex
-
- doInit() - Method in class org.deeplearning4j.nn.layers.samediff.SameDiffLayer
-
- doIteration(SparkDl4jMultiLayer, JavaRDD<DataSet>, int, int) - Method in class org.deeplearning4j.spark.impl.paramavg.ParameterAveragingTrainingMaster
-
- doIteration(SparkComputationGraph, JavaRDD<MultiDataSet>, int, int) - Method in class org.deeplearning4j.spark.impl.paramavg.ParameterAveragingTrainingMaster
-
- doIteration(SparkDl4jMultiLayer, JavaRDD<DataSet>, int, int) - Method in class org.deeplearning4j.spark.parameterserver.training.SharedTrainingMaster
-
- doIteration(SparkComputationGraph, JavaRDD<DataSet>, int, int) - Method in class org.deeplearning4j.spark.parameterserver.training.SharedTrainingMaster
-
- doIterationMDS(SparkComputationGraph, JavaRDD<MultiDataSet>, int, int) - Method in class org.deeplearning4j.spark.parameterserver.training.SharedTrainingMaster
-
- doIterationMultiPDS(SparkComputationGraph, JavaRDD<PortableDataStream>, int, int) - Method in class org.deeplearning4j.spark.parameterserver.training.SharedTrainingMaster
-
- doIterationPaths(SparkDl4jMultiLayer, SparkComputationGraph, JavaRDD<String>, int, int, int) - Method in class org.deeplearning4j.spark.impl.paramavg.ParameterAveragingTrainingMaster
-
- doIterationPaths(SparkDl4jMultiLayer, SparkComputationGraph, JavaRDD<String>, int, int, int) - Method in class org.deeplearning4j.spark.parameterserver.training.SharedTrainingMaster
-
- doIterationPathsMDS(SparkComputationGraph, JavaRDD<String>, int, int, int) - Method in class org.deeplearning4j.spark.impl.paramavg.ParameterAveragingTrainingMaster
-
- doIterationPathsMDS(SparkComputationGraph, JavaRDD<String>, int, int, int) - Method in class org.deeplearning4j.spark.parameterserver.training.SharedTrainingMaster
-
- doIterationPDS(SparkDl4jMultiLayer, SparkComputationGraph, JavaRDD<PortableDataStream>, int, int) - Method in class org.deeplearning4j.spark.impl.paramavg.ParameterAveragingTrainingMaster
-
- doIterationPDS(SparkDl4jMultiLayer, SparkComputationGraph, JavaRDD<PortableDataStream>, int, int) - Method in class org.deeplearning4j.spark.parameterserver.training.SharedTrainingMaster
-
- doIterationPDS_MDS(SparkComputationGraph, JavaRDD<PortableDataStream>, int, int) - Method in class org.deeplearning4j.spark.impl.paramavg.ParameterAveragingTrainingMaster
-
- dot(double[], double[]) - Static method in class org.ansj.util.MatrixUtil
-
- dot(float[], float[]) - Static method in class org.ansj.util.MatrixUtil
-
- doTruncatedBPTT(INDArray[], INDArray[], INDArray[], INDArray[], LayerWorkspaceMgr) - Method in class org.deeplearning4j.nn.graph.ComputationGraph
-
Fit the network using truncated BPTT
- doTruncatedBPTT(INDArray, INDArray, INDArray, INDArray, LayerWorkspaceMgr) - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
-
- DOUBLE_ARRAY_TRIE_FILENAME - Static variable in class com.atilika.kuromoji.trie.DoubleArrayTrie
-
- doubleArrayTrie - Variable in class com.atilika.kuromoji.TokenizerBase.Builder
-
- DoubleArrayTrie - Class in com.atilika.kuromoji.trie
-
- DoubleArrayTrie() - Constructor for class com.atilika.kuromoji.trie.DoubleArrayTrie
-
- DoubleArrayTrie(boolean) - Constructor for class com.atilika.kuromoji.trie.DoubleArrayTrie
-
- DoubleArrayTrieCompiler - Class in com.atilika.kuromoji.compile
-
- DoubleArrayTrieCompiler() - Constructor for class com.atilika.kuromoji.compile.DoubleArrayTrieCompiler
-
- DoublesDataSetIterator - Class in org.deeplearning4j.datasets.iterator
-
- DoublesDataSetIterator(Iterable<Pair<double[], double[]>>, int) - Constructor for class org.deeplearning4j.datasets.iterator.DoublesDataSetIterator
-
- download(String, String, File) - Method in class org.deeplearning4j.aws.s3.reader.S3Downloader
-
- download(String, String, OutputStream) - Method in class org.deeplearning4j.aws.s3.reader.S3Downloader
-
- downloadAndExtract() - Method in class org.deeplearning4j.datasets.fetchers.CacheableExtractableDataSetFetcher
-
- downloadAndExtract(DataSetType) - Method in class org.deeplearning4j.datasets.fetchers.CacheableExtractableDataSetFetcher
-
Downloads and extracts the local dataset.
- downloadAndUntar() - Static method in class com.atilika.kuromoji.util.KuromojiBinFilesFetcher
-
- downloadAndUntar() - Method in class org.deeplearning4j.base.MnistFetcher
-
- downloadFolder(String, String, File) - Method in class org.deeplearning4j.aws.s3.reader.S3Downloader
-
- drainTo(Collection<? super E>) - Method in class org.deeplearning4j.optimize.solvers.accumulation.FancyBlockingQueue
-
- drainTo(Collection<? super E>, int) - Method in class org.deeplearning4j.optimize.solvers.accumulation.FancyBlockingQueue
-
- drainTo(Collection<? super T>) - Method in class org.deeplearning4j.parallelism.MagicQueue
-
Deprecated.
- drainTo(Collection<? super T>, int) - Method in class org.deeplearning4j.parallelism.MagicQueue
-
Deprecated.
- driver - Variable in class org.deeplearning4j.spark.models.sequencevectors.functions.CountFunction
-
- driver - Variable in class org.deeplearning4j.spark.models.sequencevectors.functions.PartitionTrainingFunction
-
- driver - Variable in class org.deeplearning4j.spark.models.sequencevectors.functions.TrainingFunction
-
- driver - Variable in class org.deeplearning4j.spark.models.sequencevectors.learning.elements.SparkSkipGram
-
- driver - Variable in class org.deeplearning4j.spark.parameterserver.pw.SharedTrainingWrapper
-
- DropConnect - Class in org.deeplearning4j.nn.conf.weightnoise
-
DropConnect, based on Wan et.
- DropConnect(double) - Constructor for class org.deeplearning4j.nn.conf.weightnoise.DropConnect
-
- DropConnect(double, boolean) - Constructor for class org.deeplearning4j.nn.conf.weightnoise.DropConnect
-
- DropConnect(ISchedule) - Constructor for class org.deeplearning4j.nn.conf.weightnoise.DropConnect
-
- DropConnect(ISchedule, boolean) - Constructor for class org.deeplearning4j.nn.conf.weightnoise.DropConnect
-
- Dropout - Class in org.deeplearning4j.nn.conf.dropout
-
Implements standard (inverted) dropout.
Regarding dropout probability.
- Dropout(double) - Constructor for class org.deeplearning4j.nn.conf.dropout.Dropout
-
- Dropout(ISchedule) - Constructor for class org.deeplearning4j.nn.conf.dropout.Dropout
-
- Dropout(double, ISchedule) - Constructor for class org.deeplearning4j.nn.conf.dropout.Dropout
-
- dropOut(double) - Method in class org.deeplearning4j.nn.conf.layers.Layer.Builder
-
Dropout probability.
- dropOut(IDropout) - Method in class org.deeplearning4j.nn.conf.layers.Layer.Builder
-
Set the dropout for all layers in this network
- dropOut(double) - Method in class org.deeplearning4j.nn.conf.NeuralNetConfiguration.Builder
-
Dropout probability.
- dropOut(IDropout) - Method in class org.deeplearning4j.nn.conf.NeuralNetConfiguration.Builder
-
Set the dropout for all layers in this network
Note: values set by this method will be applied to all applicable layers in the network, unless a different
value is explicitly set on a given layer.
- DROPOUT - Static variable in class org.deeplearning4j.nn.layers.recurrent.CudnnLSTMHelper
-
- dropout - Variable in class org.deeplearning4j.nn.modelimport.keras.KerasLayer
-
- dropout(IDropout) - Method in class org.deeplearning4j.nn.transferlearning.FineTuneConfiguration.Builder
-
Set the dropout
- dropOut(double) - Method in class org.deeplearning4j.nn.transferlearning.FineTuneConfiguration.Builder
-
Dropout probability.
- dropout - Variable in class org.deeplearning4j.nn.transferlearning.FineTuneConfiguration
-
- dropoutApplied - Variable in class org.deeplearning4j.nn.layers.AbstractLayer
-
- DropoutLayer - Class in org.deeplearning4j.nn.conf.layers
-
- DropoutLayer - Class in org.deeplearning4j.nn.layers
-
Created by davekale on 12/7/16.
- DropoutLayer(NeuralNetConfiguration) - Constructor for class org.deeplearning4j.nn.layers.DropoutLayer
-
- DropoutLayer(NeuralNetConfiguration, INDArray) - Constructor for class org.deeplearning4j.nn.layers.DropoutLayer
-
- DropoutLayer.Builder - Class in org.deeplearning4j.nn.conf.layers
-
- dropoutMask - Variable in class org.deeplearning4j.nn.layers.AbstractLayer
-
- ds - Variable in class org.deeplearning4j.datasets.iterator.MultipleEpochsIterator
-
Deprecated.
- ds - Variable in class org.deeplearning4j.optimize.listeners.EvaluativeListener
-
- dsIterator - Variable in class org.deeplearning4j.optimize.listeners.EvaluativeListener
-
- dummyBias - Variable in class org.deeplearning4j.nn.layers.convolution.ConvolutionLayer
-
- dummyBiasGrad - Variable in class org.deeplearning4j.nn.layers.convolution.ConvolutionLayer
-
- DummyPreProcessor - Class in org.deeplearning4j.datasets.iterator
-
This is special dummy preProcessor, that does nothing.
- DummyPreProcessor() - Constructor for class org.deeplearning4j.datasets.iterator.DummyPreProcessor
-
- DuplicateToTimeSeriesVertex - Class in org.deeplearning4j.nn.conf.graph.rnn
-
DuplicateToTimeSeriesVertex is a vertex that goes from 2d activations to a 3d time series activations, by means of
duplication.
- DuplicateToTimeSeriesVertex(String) - Constructor for class org.deeplearning4j.nn.conf.graph.rnn.DuplicateToTimeSeriesVertex
-
- DuplicateToTimeSeriesVertex - Class in org.deeplearning4j.nn.graph.vertex.impl.rnn
-
DuplicateToTimeSeriesVertex is a vertex that goes from 2d activations to a 3d time series activations, by means of
duplication.
- DuplicateToTimeSeriesVertex(ComputationGraph, String, int, String) - Constructor for class org.deeplearning4j.nn.graph.vertex.impl.rnn.DuplicateToTimeSeriesVertex
-
- DuplicateToTimeSeriesVertex(ComputationGraph, String, int, VertexIndices[], VertexIndices[], String) - Constructor for class org.deeplearning4j.nn.graph.vertex.impl.rnn.DuplicateToTimeSeriesVertex
-
- durationMs - Variable in class org.deeplearning4j.spark.stats.BaseEventStats
-
- E - Static variable in class org.ansj.app.crf.Config
-
- E - Static variable in class org.ansj.util.Graph
-
- eachDoc(Function<List<T>, Void>, Executor) - Method in interface org.deeplearning4j.text.invertedindex.InvertedIndex
-
Iterate over each document
- eachDocWithLabel(Function<Pair<List<T>, String>, Void>, Executor) - Method in interface org.deeplearning4j.text.invertedindex.InvertedIndex
-
Iterate over each document with a label
- eachDocWithLabels(Function<Pair<List<T>, Collection<String>>, Void>, Executor) - Method in interface org.deeplearning4j.text.invertedindex.InvertedIndex
-
Iterate over each document with a label
- EarlyStoppingConfiguration<T extends Model> - Class in org.deeplearning4j.earlystopping
-
Early stopping configuration: Specifies the various configuration options for running training with early stopping.
Users need to specify the following:
(a) EarlyStoppingModelSaver: How models will be saved (to disk, to memory, etc) (Default: in memory)
(b) Termination conditions: at least one termination condition must be specified
(i) Iteration termination conditions: calculated once for each minibatch.
- EarlyStoppingConfiguration.Builder<T extends Model> - Class in org.deeplearning4j.earlystopping
-
- EarlyStoppingGraphTrainer - Class in org.deeplearning4j.earlystopping.trainer
-
Class for conducting early stopping training locally (single machine).
Can be used to train a
ComputationGraph
- EarlyStoppingGraphTrainer(EarlyStoppingConfiguration<ComputationGraph>, ComputationGraph, DataSetIterator) - Constructor for class org.deeplearning4j.earlystopping.trainer.EarlyStoppingGraphTrainer
-
- EarlyStoppingGraphTrainer(EarlyStoppingConfiguration<ComputationGraph>, ComputationGraph, DataSetIterator, EarlyStoppingListener<ComputationGraph>) - Constructor for class org.deeplearning4j.earlystopping.trainer.EarlyStoppingGraphTrainer
-
Constructor for training using a DataSetIterator
- EarlyStoppingGraphTrainer(EarlyStoppingConfiguration<ComputationGraph>, ComputationGraph, MultiDataSetIterator, EarlyStoppingListener<ComputationGraph>) - Constructor for class org.deeplearning4j.earlystopping.trainer.EarlyStoppingGraphTrainer
-
Constructor for training using a MultiDataSetIterator
- EarlyStoppingListener<T extends Model> - Interface in org.deeplearning4j.earlystopping.listener
-
EarlyStoppingListener is a listener interface for conducting early stopping training.
- EarlyStoppingModelSaver<T extends Model> - Interface in org.deeplearning4j.earlystopping
-
Interface for saving MultiLayerNetworks learned during early stopping, and retrieving them again later
- EarlyStoppingParallelTrainer<T extends Model> - Class in org.deeplearning4j.parallelism
-
- EarlyStoppingParallelTrainer(EarlyStoppingConfiguration<T>, T, DataSetIterator, MultiDataSetIterator, int, int, int) - Constructor for class org.deeplearning4j.parallelism.EarlyStoppingParallelTrainer
-
- EarlyStoppingParallelTrainer(EarlyStoppingConfiguration<T>, T, DataSetIterator, MultiDataSetIterator, EarlyStoppingListener<T>, int, int, int) - Constructor for class org.deeplearning4j.parallelism.EarlyStoppingParallelTrainer
-
- EarlyStoppingParallelTrainer(EarlyStoppingConfiguration<T>, T, DataSetIterator, MultiDataSetIterator, EarlyStoppingListener<T>, int, int, int, boolean, boolean) - Constructor for class org.deeplearning4j.parallelism.EarlyStoppingParallelTrainer
-
- EarlyStoppingResult<T extends Model> - Class in org.deeplearning4j.earlystopping
-
EarlyStoppingResult: contains the results of the early stopping training, such as:
- Why the training was terminated
- Score vs.
- EarlyStoppingResult(EarlyStoppingResult.TerminationReason, String, Map<Integer, Double>, int, double, int, T) - Constructor for class org.deeplearning4j.earlystopping.EarlyStoppingResult
-
- EarlyStoppingResult.TerminationReason - Enum in org.deeplearning4j.earlystopping
-
- EarlyStoppingTrainer - Class in org.deeplearning4j.earlystopping.trainer
-
Class for conducting early stopping training locally (single machine), for training a
MultiLayerNetwork.
- EarlyStoppingTrainer(EarlyStoppingConfiguration<MultiLayerNetwork>, MultiLayerConfiguration, DataSetIterator) - Constructor for class org.deeplearning4j.earlystopping.trainer.EarlyStoppingTrainer
-
- EarlyStoppingTrainer(EarlyStoppingConfiguration<MultiLayerNetwork>, MultiLayerNetwork, DataSetIterator) - Constructor for class org.deeplearning4j.earlystopping.trainer.EarlyStoppingTrainer
-
- EarlyStoppingTrainer(EarlyStoppingConfiguration<MultiLayerNetwork>, MultiLayerNetwork, DataSetIterator, EarlyStoppingListener<MultiLayerNetwork>) - Constructor for class org.deeplearning4j.earlystopping.trainer.EarlyStoppingTrainer
-
- EarlyTerminationDataSetIterator - Class in org.deeplearning4j.datasets.iterator
-
Builds an iterator that terminates once the number of minibatches returned with .next() is equal to a specified number
Note that a call to .next(num) is counted as a call to return a minibatch regardless of the value of num
This essentially restricts the data to this specified number of minibatches.
- EarlyTerminationDataSetIterator(DataSetIterator, int) - Constructor for class org.deeplearning4j.datasets.iterator.EarlyTerminationDataSetIterator
-
Constructor takes the iterator to wrap and the number of minibatches after which the call to hasNext()
will return false
- EarlyTerminationMultiDataSetIterator - Class in org.deeplearning4j.datasets.iterator
-
Builds an iterator that terminates once the number of minibatches returned with .next() is equal to a specified number
Note that a call to .next(num) is counted as a call to return a minibatch regardless of the value of num
This essentially restricts the data to this specified number of minibatches.
- EarlyTerminationMultiDataSetIterator(MultiDataSetIterator, int) - Constructor for class org.deeplearning4j.datasets.iterator.EarlyTerminationMultiDataSetIterator
-
Constructor takes the iterator to wrap and the number of minibatches after which the call to hasNext()
will return false
- Ec2BoxCreator - Class in org.deeplearning4j.aws.ec2
-
Creates Ec2Boxes
- Ec2BoxCreator(int, String, String, String) - Constructor for class org.deeplearning4j.aws.ec2.Ec2BoxCreator
-
- Ec2BoxCreator(String, int, String, String, String) - Constructor for class org.deeplearning4j.aws.ec2.Ec2BoxCreator
-
- Edge<T> - Class in org.deeplearning4j.graph.api
-
Edge in a graph.
- Edge(int, int, T, boolean) - Constructor for class org.deeplearning4j.graph.api.Edge
-
- Edge<T extends Number> - Class in org.deeplearning4j.models.sequencevectors.graph.primitives
-
Edge in a graph.
- Edge(int, int, T, boolean) - Constructor for class org.deeplearning4j.models.sequencevectors.graph.primitives.Edge
-
- EdgeLineProcessor<E> - Interface in org.deeplearning4j.graph.data
-
EdgeLineProcessor is used during data loading from a file, where each edge is on a separate line
Provides flexibility in loading graphs with arbitrary objects/properties that can be represented in a text format
Can also be used handle conversion of edges between non-numeric vertices to an appropriate numbered format
- effectiveKernelSize(int[], int[]) - Static method in class org.deeplearning4j.util.ConvolutionUtils
-
- ela - Variable in class org.deeplearning4j.spark.models.sequencevectors.functions.CountFunction
-
- ela - Variable in class org.deeplearning4j.spark.models.sequencevectors.SparkSequenceVectors
-
- Element - Class in org.ansj.app.crf.pojo
-
- Element(char) - Constructor for class org.ansj.app.crf.pojo.Element
-
- Element(Character, int) - Constructor for class org.ansj.app.crf.pojo.Element
-
- element() - Method in class org.deeplearning4j.optimize.solvers.accumulation.FancyBlockingQueue
-
- element() - Method in class org.deeplearning4j.parallelism.MagicQueue
-
Deprecated.
- element() - Method in class org.deeplearning4j.util.DiskBasedQueue
-
- elementAtIndex(int) - Method in class org.deeplearning4j.models.word2vec.wordstore.inmemory.AbstractCache
-
Returns SequenceElement at specified index
- elementAtIndex(int) - Method in class org.deeplearning4j.models.word2vec.wordstore.inmemory.InMemoryLookupCache
-
Deprecated.
- elementAtIndex(int) - Method in interface org.deeplearning4j.models.word2vec.wordstore.VocabCache
-
Returns SequenceElement at the given index or null
- elementFrequency - Variable in class org.deeplearning4j.models.sequencevectors.sequence.SequenceElement
-
- elements - Variable in class org.deeplearning4j.models.sequencevectors.sequence.Sequence
-
- elementsFreqAccum - Variable in class org.deeplearning4j.spark.models.sequencevectors.SparkSequenceVectors
-
- elementsFreqAccumExtra - Variable in class org.deeplearning4j.spark.models.sequencevectors.SparkSequenceVectors
-
- ElementsFrequenciesAccumulator - Class in org.deeplearning4j.spark.models.sequencevectors.functions
-
Accumulator for elements count
- ElementsFrequenciesAccumulator() - Constructor for class org.deeplearning4j.spark.models.sequencevectors.functions.ElementsFrequenciesAccumulator
-
- ElementsLearningAlgorithm<T extends SequenceElement> - Interface in org.deeplearning4j.models.embeddings.learning
-
Implementations of this interface should contain element-related learning algorithms.
- elementsLearningAlgorithm(String) - Method in class org.deeplearning4j.models.node2vec.Node2Vec.Builder
-
Deprecated.
- elementsLearningAlgorithm(ElementsLearningAlgorithm<V>) - Method in class org.deeplearning4j.models.node2vec.Node2Vec.Builder
-
Deprecated.
- elementsLearningAlgorithm(ElementsLearningAlgorithm<VocabWord>) - Method in class org.deeplearning4j.models.paragraphvectors.ParagraphVectors.Builder
-
- elementsLearningAlgorithm(String) - Method in class org.deeplearning4j.models.paragraphvectors.ParagraphVectors.Builder
-
- elementsLearningAlgorithm - Variable in class org.deeplearning4j.models.sequencevectors.SequenceVectors.Builder
-
- elementsLearningAlgorithm(String) - Method in class org.deeplearning4j.models.sequencevectors.SequenceVectors.Builder
-
* Sets specific LearningAlgorithm as Elements Learning Algorithm
- elementsLearningAlgorithm(ElementsLearningAlgorithm<T>) - Method in class org.deeplearning4j.models.sequencevectors.SequenceVectors.Builder
-
* Sets specific LearningAlgorithm as Elements Learning Algorithm
- elementsLearningAlgorithm - Variable in class org.deeplearning4j.models.sequencevectors.SequenceVectors
-
- elementsLearningAlgorithm(String) - Method in class org.deeplearning4j.models.word2vec.Word2Vec.Builder
-
- elementsLearningAlgorithm(ElementsLearningAlgorithm<VocabWord>) - Method in class org.deeplearning4j.models.word2vec.Word2Vec.Builder
-
- elementsLearningAlgorithm - Variable in class org.deeplearning4j.spark.models.sequencevectors.functions.PartitionTrainingFunction
-
- elementsLearningAlgorithm - Variable in class org.deeplearning4j.spark.models.sequencevectors.functions.TrainingFunction
-
- elementsLearningAlgorithm - Variable in class org.deeplearning4j.spark.models.sequencevectors.learning.sequence.BaseSparkSequenceLearningAlgorithm
-
- elementsMap - Variable in class org.deeplearning4j.models.sequencevectors.sequence.Sequence
-
- ElementWiseMultiplicationLayer - Class in org.deeplearning4j.nn.conf.layers.misc
-
Elementwise multiplication layer with weights: implements out = activationFn(input .* w + b) where:
- w is a learnable weight vector of length nOut
- ".*" is element-wise multiplication
- b is a bias vector
Note that the input and output sizes of the element-wise layer are the same for this layer
- ElementWiseMultiplicationLayer() - Constructor for class org.deeplearning4j.nn.conf.layers.misc.ElementWiseMultiplicationLayer
-
- ElementWiseMultiplicationLayer(ElementWiseMultiplicationLayer.Builder) - Constructor for class org.deeplearning4j.nn.conf.layers.misc.ElementWiseMultiplicationLayer
-
- ElementWiseMultiplicationLayer - Class in org.deeplearning4j.nn.layers.feedforward.elementwise
-
Elementwise multiplication layer with weights: implements out = activationFn(input .* w + b) where:
- w is a learnable weight vector of length nOut
- ".*" is element-wise multiplication
- b is a bias vector
Note that the input and output sizes of the element-wise layer are the same for this layer
- ElementWiseMultiplicationLayer(NeuralNetConfiguration) - Constructor for class org.deeplearning4j.nn.layers.feedforward.elementwise.ElementWiseMultiplicationLayer
-
- ElementWiseMultiplicationLayer(NeuralNetConfiguration, INDArray) - Constructor for class org.deeplearning4j.nn.layers.feedforward.elementwise.ElementWiseMultiplicationLayer
-
- ElementWiseMultiplicationLayer.Builder - Class in org.deeplearning4j.nn.conf.layers.misc
-
- ElementWiseParamInitializer - Class in org.deeplearning4j.nn.params
-
created by jingshu
- ElementWiseParamInitializer() - Constructor for class org.deeplearning4j.nn.params.ElementWiseParamInitializer
-
- ElementWiseVertex - Class in org.deeplearning4j.nn.conf.graph
-
An ElementWiseVertex is used to combine the activations of two or more layer in an element-wise manner
For example, the activations may be combined by addition, subtraction or multiplication or by selecting the maximum.
- ElementWiseVertex(ElementWiseVertex.Op) - Constructor for class org.deeplearning4j.nn.conf.graph.ElementWiseVertex
-
- ElementWiseVertex - Class in org.deeplearning4j.nn.graph.vertex.impl
-
An ElementWiseVertex is used to combine the activations of two or more layer in an element-wise manner
For example, the activations may be combined by addition, subtraction or multiplication or by selecting the maximum.
- ElementWiseVertex(ComputationGraph, String, int, ElementWiseVertex.Op) - Constructor for class org.deeplearning4j.nn.graph.vertex.impl.ElementWiseVertex
-
- ElementWiseVertex(ComputationGraph, String, int, VertexIndices[], VertexIndices[], ElementWiseVertex.Op) - Constructor for class org.deeplearning4j.nn.graph.vertex.impl.ElementWiseVertex
-
- ElementWiseVertex.Op - Enum in org.deeplearning4j.nn.conf.graph
-
- ElementWiseVertex.Op - Enum in org.deeplearning4j.nn.graph.vertex.impl
-
- EmailRecognition - Class in org.ansj.recognition.impl
-
电子邮箱抽取
- EmailRecognition() - Constructor for class org.ansj.recognition.impl.EmailRecognition
-
- EmbeddedStemmingPreprocessor - Class in org.deeplearning4j.text.tokenization.tokenizer.preprocessor
-
This tokenizer preprocessor uses given preprocessor + does english Porter stemming on tokens on top of it
- EmbeddedStemmingPreprocessor(TokenPreProcess) - Constructor for class org.deeplearning4j.text.tokenization.tokenizer.preprocessor.EmbeddedStemmingPreprocessor
-
- EmbeddingLayer - Class in org.deeplearning4j.nn.conf.layers
-
Embedding layer: feed-forward layer that expects single integers per example as input (class numbers, in range 0 to numClass-1)
as input.
- EmbeddingLayer - Class in org.deeplearning4j.nn.layers.feedforward.embedding
-
Embedding layer: feed-forward layer that expects single integers per example as input (class numbers, in range 0 to numClass-1)
as input.
- EmbeddingLayer(NeuralNetConfiguration) - Constructor for class org.deeplearning4j.nn.layers.feedforward.embedding.EmbeddingLayer
-
- EmbeddingLayer.Builder - Class in org.deeplearning4j.nn.conf.layers
-
- EmbeddingSequenceLayer - Class in org.deeplearning4j.nn.conf.layers
-
Embedding layer for sequences: feed-forward layer that expects fixed-length number (inputLength) of integers/indices
per example as input, ranged from 0 to numClasses - 1.
- EmbeddingSequenceLayer - Class in org.deeplearning4j.nn.layers.feedforward.embedding
-
Embedding layer for sequences: feed-forward layer that expects fixed-length number (inputLength) of integers/indices
per example as input, ranged from 0 to numClasses - 1.
- EmbeddingSequenceLayer(NeuralNetConfiguration) - Constructor for class org.deeplearning4j.nn.layers.feedforward.embedding.EmbeddingSequenceLayer
-
- EmbeddingSequenceLayer.Builder - Class in org.deeplearning4j.nn.conf.layers
-
- EMNIST_ROOT - Static variable in class org.deeplearning4j.datasets.fetchers.EmnistDataFetcher
-
- EmnistDataFetcher - Class in org.deeplearning4j.datasets.fetchers
-
Data fetcher for the EMNIST dataset
- EmnistDataFetcher(EmnistDataSetIterator.Set, boolean, boolean, boolean, long) - Constructor for class org.deeplearning4j.datasets.fetchers.EmnistDataFetcher
-
- EmnistDataSetIterator - Class in org.deeplearning4j.datasets.iterator.impl
-
- EmnistDataSetIterator(EmnistDataSetIterator.Set, int, boolean) - Constructor for class org.deeplearning4j.datasets.iterator.impl.EmnistDataSetIterator
-
- EmnistDataSetIterator(EmnistDataSetIterator.Set, int, boolean, long) - Constructor for class org.deeplearning4j.datasets.iterator.impl.EmnistDataSetIterator
-
- EmnistDataSetIterator(EmnistDataSetIterator.Set, int, boolean, boolean, boolean, long) - Constructor for class org.deeplearning4j.datasets.iterator.impl.EmnistDataSetIterator
-
Get the specified number of MNIST examples (test or train set), with optional shuffling and binarization.
- EmnistDataSetIterator.Set - Enum in org.deeplearning4j.datasets.iterator.impl
-
EMNIST dataset has multiple different subsets.
- EmnistFetcher - Class in org.deeplearning4j.base
-
Downloader for EMNIST dataset
- EmnistFetcher(EmnistDataSetIterator.Set) - Constructor for class org.deeplearning4j.base.EmnistFetcher
-
- EMPTY_BYTES - Static variable in class org.deeplearning4j.ui.stats.impl.SbeUtil
-
- EmptyParamInitializer - Class in org.deeplearning4j.nn.params
-
- EmptyParamInitializer() - Constructor for class org.deeplearning4j.nn.params.EmptyParamInitializer
-
- EmrConfig - Class in org.deeplearning4j.aws.emr
-
- EmrConfig() - Constructor for class org.deeplearning4j.aws.emr.EmrConfig
-
- emrConfigs(List<EmrConfig>) - Method in class org.deeplearning4j.aws.emr.SparkEMRClient.Builder
-
A list of configuration parameters to apply to EMR instances.
- emrRelease(String) - Method in class org.deeplearning4j.aws.emr.SparkEMRClient.Builder
-
Defines the EMR release version to be used in this cluster
uses a release label
See https://docs.aws.amazon.com/emr/latest/ReleaseGuide/emr-4.2.0/emr-release-differences.html#emr-release-label
- emrServiceRole(String) - Method in class org.deeplearning4j.aws.emr.SparkEMRClient.Builder
-
Defines the IAM role to be assumed by the EMR service
- EN - Static variable in class org.ansj.domain.TermNature
-
- EN - Static variable in class org.ansj.domain.TermNatures
-
- EN_BEGIN - Static variable in class org.ansj.app.crf.Config
-
- enableHttps(boolean) - Method in class org.deeplearning4j.ui.UiConnectionInfo.Builder
-
- enableRemoteListener() - Method in class org.deeplearning4j.ui.api.UIServer
-
Enable the remote listener functionality, storing all data in memory, and attaching the instance to the UI.
- enableRemoteListener(StatsStorageRouter, boolean) - Method in class org.deeplearning4j.ui.api.UIServer
-
Enable the remote listener functionality, storing the received results in the specified StatsStorageRouter.
- enableRemoteListener() - Method in class org.deeplearning4j.ui.play.PlayUIServer
-
- enableRemoteListener(StatsStorageRouter, boolean) - Method in class org.deeplearning4j.ui.play.PlayUIServer
-
- enableScavenger(boolean) - Method in class org.deeplearning4j.models.node2vec.Node2Vec.Builder
-
Deprecated.
- enableScavenger(boolean) - Method in class org.deeplearning4j.models.paragraphvectors.ParagraphVectors.Builder
-
This method ebables/disables periodical vocab truncation during construction
Default value: disabled
- enableScavenger - Variable in class org.deeplearning4j.models.sequencevectors.SequenceVectors.Builder
-
- enableScavenger(boolean) - Method in class org.deeplearning4j.models.sequencevectors.SequenceVectors.Builder
-
This method ebables/disables periodical vocab truncation during construction
Default value: disabled
- enableScavenger - Variable in class org.deeplearning4j.models.sequencevectors.SequenceVectors
-
- enableScavenger(boolean) - Method in class org.deeplearning4j.models.word2vec.Word2Vec.Builder
-
This method ebables/disables periodical vocab truncation during construction
Default value: disabled
- enableScavenger(boolean) - Method in class org.deeplearning4j.models.word2vec.wordstore.VocabConstructor.Builder
-
- encode() - Method in interface org.deeplearning4j.api.storage.Persistable
-
- encode(ByteBuffer) - Method in interface org.deeplearning4j.api.storage.Persistable
-
- encode(OutputStream) - Method in interface org.deeplearning4j.api.storage.Persistable
-
Encode this persistable in to an output stream
- encode(INDArray, boolean, LayerWorkspaceMgr) - Method in class org.deeplearning4j.nn.layers.feedforward.autoencoder.AutoEncoder
-
- encode() - Method in class org.deeplearning4j.ui.stats.impl.java.JavaStatsInitializationReport
-
- encode(ByteBuffer) - Method in class org.deeplearning4j.ui.stats.impl.java.JavaStatsInitializationReport
-
- encode(OutputStream) - Method in class org.deeplearning4j.ui.stats.impl.java.JavaStatsInitializationReport
-
- encode() - Method in class org.deeplearning4j.ui.stats.impl.java.JavaStatsReport
-
- encode(ByteBuffer) - Method in class org.deeplearning4j.ui.stats.impl.java.JavaStatsReport
-
- encode(OutputStream) - Method in class org.deeplearning4j.ui.stats.impl.java.JavaStatsReport
-
- encode() - Method in class org.deeplearning4j.ui.stats.impl.SbeStatsInitializationReport
-
- encode(ByteBuffer) - Method in class org.deeplearning4j.ui.stats.impl.SbeStatsInitializationReport
-
- encode(MutableDirectBuffer) - Method in class org.deeplearning4j.ui.stats.impl.SbeStatsInitializationReport
-
- encode(OutputStream) - Method in class org.deeplearning4j.ui.stats.impl.SbeStatsInitializationReport
-
- encode() - Method in class org.deeplearning4j.ui.stats.impl.SbeStatsReport
-
- encode(ByteBuffer) - Method in class org.deeplearning4j.ui.stats.impl.SbeStatsReport
-
- encode(MutableDirectBuffer) - Method in class org.deeplearning4j.ui.stats.impl.SbeStatsReport
-
- encode(OutputStream) - Method in class org.deeplearning4j.ui.stats.impl.SbeStatsReport
-
- encode(MutableDirectBuffer) - Method in interface org.deeplearning4j.ui.storage.AgronaPersistable
-
- encode() - Method in class org.deeplearning4j.ui.storage.impl.JavaStorageMetaData
-
- encode(ByteBuffer) - Method in class org.deeplearning4j.ui.storage.impl.JavaStorageMetaData
-
- encode(OutputStream) - Method in class org.deeplearning4j.ui.storage.impl.JavaStorageMetaData
-
- encode() - Method in class org.deeplearning4j.ui.storage.impl.SbeStorageMetaData
-
- encode(ByteBuffer) - Method in class org.deeplearning4j.ui.storage.impl.SbeStorageMetaData
-
- encode(MutableDirectBuffer) - Method in class org.deeplearning4j.ui.storage.impl.SbeStorageMetaData
-
- encode(OutputStream) - Method in class org.deeplearning4j.ui.storage.impl.SbeStorageMetaData
-
- encode() - Method in class org.deeplearning4j.ui.weights.ConvolutionListenerPersistable
-
- encode(ByteBuffer) - Method in class org.deeplearning4j.ui.weights.ConvolutionListenerPersistable
-
- encode(OutputStream) - Method in class org.deeplearning4j.ui.weights.ConvolutionListenerPersistable
-
- encodeB64(String) - Static method in class org.deeplearning4j.models.embeddings.loader.WordVectorSerializer
-
- ENCODED_LENGTH - Static variable in class org.deeplearning4j.ui.stats.sbe.GroupSizeEncodingDecoder
-
- ENCODED_LENGTH - Static variable in class org.deeplearning4j.ui.stats.sbe.GroupSizeEncodingEncoder
-
- ENCODED_LENGTH - Static variable in class org.deeplearning4j.ui.stats.sbe.InitFieldsPresentDecoder
-
- ENCODED_LENGTH - Static variable in class org.deeplearning4j.ui.stats.sbe.InitFieldsPresentEncoder
-
- ENCODED_LENGTH - Static variable in class org.deeplearning4j.ui.stats.sbe.MessageHeaderDecoder
-
- ENCODED_LENGTH - Static variable in class org.deeplearning4j.ui.stats.sbe.MessageHeaderEncoder
-
- ENCODED_LENGTH - Static variable in class org.deeplearning4j.ui.stats.sbe.UpdateFieldsPresentDecoder
-
- ENCODED_LENGTH - Static variable in class org.deeplearning4j.ui.stats.sbe.UpdateFieldsPresentEncoder
-
- ENCODED_LENGTH - Static variable in class org.deeplearning4j.ui.stats.sbe.VarDataUTF8Decoder
-
- ENCODED_LENGTH - Static variable in class org.deeplearning4j.ui.stats.sbe.VarDataUTF8Encoder
-
- EncodedGradientsAccumulator - Class in org.deeplearning4j.optimize.solvers.accumulation
-
This GradientsAccumulator is suited for CUDA backend.
- EncodedGradientsAccumulator(double) - Constructor for class org.deeplearning4j.optimize.solvers.accumulation.EncodedGradientsAccumulator
-
- EncodedGradientsAccumulator(int) - Constructor for class org.deeplearning4j.optimize.solvers.accumulation.EncodedGradientsAccumulator
-
- EncodedGradientsAccumulator(int, double) - Constructor for class org.deeplearning4j.optimize.solvers.accumulation.EncodedGradientsAccumulator
-
- EncodedGradientsAccumulator(int, MessageHandler, long, int, Double) - Constructor for class org.deeplearning4j.optimize.solvers.accumulation.EncodedGradientsAccumulator
-
- EncodedGradientsAccumulator.Builder - Class in org.deeplearning4j.optimize.solvers.accumulation
-
- encodedLength() - Method in class org.deeplearning4j.ui.stats.sbe.GroupSizeEncodingDecoder
-
- encodedLength() - Method in class org.deeplearning4j.ui.stats.sbe.GroupSizeEncodingEncoder
-
- encodedLength() - Method in class org.deeplearning4j.ui.stats.sbe.InitFieldsPresentDecoder
-
- encodedLength() - Method in class org.deeplearning4j.ui.stats.sbe.InitFieldsPresentEncoder
-
- encodedLength() - Method in class org.deeplearning4j.ui.stats.sbe.MessageHeaderDecoder
-
- encodedLength() - Method in class org.deeplearning4j.ui.stats.sbe.MessageHeaderEncoder
-
- encodedLength() - Method in class org.deeplearning4j.ui.stats.sbe.StaticInfoDecoder
-
- encodedLength() - Method in class org.deeplearning4j.ui.stats.sbe.StaticInfoEncoder
-
- encodedLength() - Method in class org.deeplearning4j.ui.stats.sbe.StorageMetaDataDecoder
-
- encodedLength() - Method in class org.deeplearning4j.ui.stats.sbe.StorageMetaDataEncoder
-
- encodedLength() - Method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder
-
- encodedLength() - Method in class org.deeplearning4j.ui.stats.sbe.UpdateEncoder
-
- encodedLength() - Method in class org.deeplearning4j.ui.stats.sbe.UpdateFieldsPresentDecoder
-
- encodedLength() - Method in class org.deeplearning4j.ui.stats.sbe.UpdateFieldsPresentEncoder
-
- encodedLength() - Method in class org.deeplearning4j.ui.stats.sbe.VarDataUTF8Decoder
-
- encodedLength() - Method in class org.deeplearning4j.ui.stats.sbe.VarDataUTF8Encoder
-
- ENCODER_PREFIX - Static variable in class org.deeplearning4j.nn.params.VariationalAutoencoderParamInitializer
-
- encoderLayerSizes(int...) - Method in class org.deeplearning4j.nn.conf.layers.variational.VariationalAutoencoder.Builder
-
Size of the encoder layers, in units.
- encoderLayerSizes - Variable in class org.deeplearning4j.nn.layers.variational.VariationalAutoencoder
-
- encodeUpdates(INDArray) - Method in class org.deeplearning4j.optimize.solvers.accumulation.EncodingHandler
-
- EncodingHandler - Class in org.deeplearning4j.optimize.solvers.accumulation
-
This MessageHandler implementation is suited for debugging mostly, but still can be used in production environment if you really want that.
- EncodingHandler() - Constructor for class org.deeplearning4j.optimize.solvers.accumulation.EncodingHandler
-
This method builds new EncodingHandler instance with initial threshold of 1e-3
- EncodingHandler(double) - Constructor for class org.deeplearning4j.optimize.solvers.accumulation.EncodingHandler
-
This method builds new EncodingHandler instance
- EncodingHandler(double, Double) - Constructor for class org.deeplearning4j.optimize.solvers.accumulation.EncodingHandler
-
This method builds new EncodingHandler instance
- EncodingHandler(double, double, double, double, int, int) - Constructor for class org.deeplearning4j.optimize.solvers.accumulation.EncodingHandler
-
This method builds new EncodingHandler instance
- EncodingHandler(double, double, double, double, int, int, Double) - Constructor for class org.deeplearning4j.optimize.solvers.accumulation.EncodingHandler
-
This method builds new EncodingHandler instance
- encodingLengthBytes() - Method in interface org.deeplearning4j.api.storage.Persistable
-
- encodingLengthBytes() - Method in class org.deeplearning4j.ui.stats.impl.java.JavaStatsInitializationReport
-
- encodingLengthBytes() - Method in class org.deeplearning4j.ui.stats.impl.java.JavaStatsReport
-
- encodingLengthBytes() - Method in class org.deeplearning4j.ui.stats.impl.SbeStatsInitializationReport
-
- encodingLengthBytes() - Method in class org.deeplearning4j.ui.stats.impl.SbeStatsReport
-
- encodingLengthBytes() - Method in class org.deeplearning4j.ui.storage.impl.JavaStorageMetaData
-
- encodingLengthBytes() - Method in class org.deeplearning4j.ui.storage.impl.SbeStorageMetaData
-
- encodingLengthBytes() - Method in class org.deeplearning4j.ui.weights.ConvolutionListenerPersistable
-
- encodingThreshold(double) - Method in class org.deeplearning4j.optimize.solvers.accumulation.EncodedGradientsAccumulator.Builder
-
This method allows to set encoding threshold for this accumulator instance
Default value: 1e-3
- encryption(String) - Static method in class org.ansj.dic.impl.Jdbc2Stream
-
- end() - Static method in class com.atilika.kuromoji.compile.ProgressLog
-
- END - Static variable in class org.ansj.app.crf.Config
-
- END - Static variable in class org.ansj.domain.AnsjItem
-
- end - Variable in class org.ansj.domain.PersonNatureAttr
-
- END - Static variable in class org.ansj.domain.TermNature
-
- END - Static variable in class org.ansj.domain.TermNatures
-
- end - Variable in class org.ansj.splitWord.impl.GetWordsImpl
-
- end - Variable in class org.ansj.util.Graph
-
- EndingPreProcessor - Class in org.deeplearning4j.text.tokenization.tokenizer.preprocessor
-
Gets rid of endings:
ed,ing, ly, s, .
- EndingPreProcessor() - Constructor for class org.deeplearning4j.text.tokenization.tokenizer.preprocessor.EndingPreProcessor
-
- endWhenDistributionVariationRateLessThan(double) - Method in class org.deeplearning4j.clustering.strategy.BaseClusteringStrategy
-
- endWhenDistributionVariationRateLessThan(double) - Method in interface org.deeplearning4j.clustering.strategy.ClusteringStrategy
-
- endWhenIterationCountEquals(int) - Method in class org.deeplearning4j.clustering.strategy.BaseClusteringStrategy
-
- endWhenIterationCountEquals(int) - Method in interface org.deeplearning4j.clustering.strategy.ClusteringStrategy
-
- enforceSingleDevice(boolean) - Method in class org.deeplearning4j.datasets.iterator.parallel.JointParallelDataSetIterator.Builder
-
- enforceSingleDevice - Variable in class org.deeplearning4j.datasets.iterator.parallel.JointParallelDataSetIterator
-
- enforceTrainingConfig - Variable in class org.deeplearning4j.nn.modelimport.keras.KerasModel
-
- enforceTrainingConfig - Variable in class org.deeplearning4j.nn.modelimport.keras.utils.KerasModelBuilder
-
- enforceTrainingConfig(boolean) - Method in class org.deeplearning4j.nn.modelimport.keras.utils.KerasModelBuilder
-
- enlarge(double) - Method in class org.deeplearning4j.clustering.kdtree.HyperRect.Interval
-
- enlargeTo(INDArray) - Method in class org.deeplearning4j.clustering.kdtree.HyperRect
-
- enqueueGradient(SharedGradient) - Method in interface org.deeplearning4j.parallelism.trainer.CommunicativeTrainer
-
- enqueueGradient(SharedGradient) - Method in class org.deeplearning4j.parallelism.trainer.SymmetricTrainer
-
Deprecated.
- entries - Variable in class com.atilika.kuromoji.trie.PatriciaTrie
-
Number of entries in the trie
- entropy(INDArray) - Method in class org.deeplearning4j.clustering.lsh.RandomProjectionLSH
-
This picks uniformaly distributed random points on the unit of a sphere using the method of:
An efficient method for generating uniformly distributed points on the surface of an n-dimensional sphere
JS Hicks, RF Wheeling - Communications of the ACM, 1959
- entropy(double[]) - Static method in class org.deeplearning4j.clustering.util.MathUtils
-
This returns the entropy (information gain, or uncertainty of a random variable).
- entrySet() - Method in class com.atilika.kuromoji.trie.PatriciaTrie
-
Returns a copy of the mappings contained in this trie as a Set
- ENV - Static variable in class org.ansj.util.MyStaticValue
-
- envKey() - Method in class org.deeplearning4j.ui.stats.sbe.StaticInfoDecoder.SwEnvironmentInfoDecoder
-
- envKey(String) - Method in class org.deeplearning4j.ui.stats.sbe.StaticInfoEncoder.SwEnvironmentInfoEncoder
-
- envKeyCharacterEncoding() - Static method in class org.deeplearning4j.ui.stats.sbe.StaticInfoDecoder.SwEnvironmentInfoDecoder
-
- envKeyCharacterEncoding() - Static method in class org.deeplearning4j.ui.stats.sbe.StaticInfoEncoder.SwEnvironmentInfoEncoder
-
- envKeyHeaderLength() - Static method in class org.deeplearning4j.ui.stats.sbe.StaticInfoDecoder.SwEnvironmentInfoDecoder
-
- envKeyHeaderLength() - Static method in class org.deeplearning4j.ui.stats.sbe.StaticInfoEncoder.SwEnvironmentInfoEncoder
-
- envKeyId() - Static method in class org.deeplearning4j.ui.stats.sbe.StaticInfoDecoder.SwEnvironmentInfoDecoder
-
- envKeyId() - Static method in class org.deeplearning4j.ui.stats.sbe.StaticInfoEncoder.SwEnvironmentInfoEncoder
-
- envKeyLength() - Method in class org.deeplearning4j.ui.stats.sbe.StaticInfoDecoder.SwEnvironmentInfoDecoder
-
- envKeyMetaAttribute(MetaAttribute) - Static method in class org.deeplearning4j.ui.stats.sbe.StaticInfoDecoder.SwEnvironmentInfoDecoder
-
- envKeyMetaAttribute(MetaAttribute) - Static method in class org.deeplearning4j.ui.stats.sbe.StaticInfoEncoder.SwEnvironmentInfoEncoder
-
- envValue() - Method in class org.deeplearning4j.ui.stats.sbe.StaticInfoDecoder.SwEnvironmentInfoDecoder
-
- envValue(String) - Method in class org.deeplearning4j.ui.stats.sbe.StaticInfoEncoder.SwEnvironmentInfoEncoder
-
- envValueCharacterEncoding() - Static method in class org.deeplearning4j.ui.stats.sbe.StaticInfoDecoder.SwEnvironmentInfoDecoder
-
- envValueCharacterEncoding() - Static method in class org.deeplearning4j.ui.stats.sbe.StaticInfoEncoder.SwEnvironmentInfoEncoder
-
- envValueHeaderLength() - Static method in class org.deeplearning4j.ui.stats.sbe.StaticInfoDecoder.SwEnvironmentInfoDecoder
-
- envValueHeaderLength() - Static method in class org.deeplearning4j.ui.stats.sbe.StaticInfoEncoder.SwEnvironmentInfoEncoder
-
- envValueId() - Static method in class org.deeplearning4j.ui.stats.sbe.StaticInfoDecoder.SwEnvironmentInfoDecoder
-
- envValueId() - Static method in class org.deeplearning4j.ui.stats.sbe.StaticInfoEncoder.SwEnvironmentInfoEncoder
-
- envValueLength() - Method in class org.deeplearning4j.ui.stats.sbe.StaticInfoDecoder.SwEnvironmentInfoDecoder
-
- envValueMetaAttribute(MetaAttribute) - Static method in class org.deeplearning4j.ui.stats.sbe.StaticInfoDecoder.SwEnvironmentInfoDecoder
-
- envValueMetaAttribute(MetaAttribute) - Static method in class org.deeplearning4j.ui.stats.sbe.StaticInfoEncoder.SwEnvironmentInfoEncoder
-
- epochCount - Variable in class org.deeplearning4j.nn.conf.ComputationGraphConfiguration
-
- epochCount - Variable in class org.deeplearning4j.nn.conf.MultiLayerConfiguration
-
- epochCount - Variable in class org.deeplearning4j.nn.conf.NeuralNetConfiguration
-
- epochCount - Variable in class org.deeplearning4j.nn.layers.AbstractLayer
-
- epochCount - Variable in class org.deeplearning4j.nn.layers.variational.VariationalAutoencoder
-
- epochReset - Variable in class org.deeplearning4j.spark.parameterserver.conf.SharedTrainingConfiguration
-
- epochs - Variable in class org.deeplearning4j.datasets.iterator.MultipleEpochsIterator
-
Deprecated.
- epochs(int) - Method in class org.deeplearning4j.models.glove.Glove.Builder
-
Sets the number of iteration over training corpus during training
- epochs(int) - Method in class org.deeplearning4j.models.node2vec.Node2Vec.Builder
-
Deprecated.
- epochs(int) - Method in class org.deeplearning4j.models.paragraphvectors.ParagraphVectors.Builder
-
This method defines number of epochs (iterations over whole training corpus) for training
- epochs(int) - Method in class org.deeplearning4j.models.sequencevectors.SequenceVectors.Builder
-
This method defines how much iterations should be done over whole training corpus during modelling
- epochs(int) - Method in class org.deeplearning4j.models.word2vec.Word2Vec.Builder
-
This method defines number of epochs (iterations over whole training corpus) for training
- epochs(int) - Method in class org.deeplearning4j.spark.models.embeddings.word2vec.Word2Vec.Builder
-
This method specifies number of epochs done over whole corpus
PLEASE NOTE: NOT IMPLEMENTED
- epochs(int) - Method in class org.deeplearning4j.spark.models.sequencevectors.SparkSequenceVectors.Builder
-
- epochs(int) - Method in class org.deeplearning4j.spark.models.word2vec.SparkWord2Vec.Builder
-
- EpochTerminationCondition - Interface in org.deeplearning4j.earlystopping.termination
-
Interface for termination conditions to be evaluated once per epoch (i.e., once per pass of the full data set),
based on a score and epoch number
- epochTerminationConditions(EpochTerminationCondition...) - Method in class org.deeplearning4j.earlystopping.EarlyStoppingConfiguration.Builder
-
Termination conditions to be evaluated every N epochs, with N set by evaluateEveryNEpochs option
- epochTerminationConditions(List<EpochTerminationCondition>) - Method in class org.deeplearning4j.earlystopping.EarlyStoppingConfiguration.Builder
-
Termination conditions to be evaluated every N epochs, with N set by evaluateEveryNEpochs option
- eps - Variable in class org.deeplearning4j.nn.conf.graph.L2NormalizeVertex
-
- eps - Variable in class org.deeplearning4j.nn.conf.graph.L2Vertex
-
- eps - Variable in class org.deeplearning4j.nn.conf.layers.BatchNormalization.Builder
-
- eps(double) - Method in class org.deeplearning4j.nn.conf.layers.BatchNormalization.Builder
-
Epsilon value for batch normalization; small floating point value added to variance
(algorithm 1 in http://arxiv.org/pdf/1502.03167v3.pdf) to reduce/avoid underflow issues.
Default: 1e-5
- eps - Variable in class org.deeplearning4j.nn.conf.layers.BatchNormalization
-
- eps - Variable in class org.deeplearning4j.nn.conf.layers.SubsamplingLayer.BaseSubsamplingBuilder
-
- eps(double) - Method in class org.deeplearning4j.nn.conf.layers.SubsamplingLayer.BaseSubsamplingBuilder
-
- eps - Variable in class org.deeplearning4j.nn.conf.layers.SubsamplingLayer
-
- epsilon - Variable in class org.deeplearning4j.nn.conf.constraint.BaseConstraint
-
- epsilon - Variable in class org.deeplearning4j.nn.graph.vertex.BaseGraphVertex
-
- EpsTermination - Class in org.deeplearning4j.optimize.terminations
-
Epsilon termination (absolute change based on tolerance)
- EpsTermination(double, double) - Constructor for class org.deeplearning4j.optimize.terminations.EpsTermination
-
- EpsTermination() - Constructor for class org.deeplearning4j.optimize.terminations.EpsTermination
-
- equals(Object) - Method in class org.ansj.app.keyword.Keyword
-
- equals(Object) - Method in class org.deeplearning4j.clustering.quadtree.Cell
-
- equals(Object) - Method in class org.deeplearning4j.clustering.sptree.HeapItem
-
- equals(Object) - Method in class org.deeplearning4j.clustering.sptree.HeapObject
-
- equals(Object) - Method in class org.deeplearning4j.eval.ConfusionMatrix
-
- equals(Object) - Method in class org.deeplearning4j.graph.api.Edge
-
- equals(Object) - Method in class org.deeplearning4j.graph.api.Vertex
-
- equals(Object) - Method in class org.deeplearning4j.graph.graph.Graph
-
- equals(Object) - Method in class org.deeplearning4j.models.glove.count.CoOccurrenceWeight
-
- equals(Object) - Method in class org.deeplearning4j.models.sequencevectors.graph.primitives.Edge
-
- equals(Object) - Method in class org.deeplearning4j.models.sequencevectors.graph.primitives.Graph
-
- equals(Object) - Method in class org.deeplearning4j.models.sequencevectors.graph.primitives.Vertex
-
- equals(Object) - Method in class org.deeplearning4j.models.sequencevectors.sequence.Sequence
-
- equals(Object) - Method in class org.deeplearning4j.models.sequencevectors.sequence.SequenceElement
-
Equals method override should be properly implemented for any extended class, otherwise it will be based on label equality
- equals(Object) - Method in class org.deeplearning4j.models.word2vec.VocabWord
-
- equals(Object) - Method in class org.deeplearning4j.models.word2vec.VocabWork
-
- equals(Object) - Method in class org.deeplearning4j.models.word2vec.wordstore.inmemory.InMemoryLookupCache
-
Deprecated.
- equals(Object) - Method in class org.deeplearning4j.models.word2vec.wordstore.VocabularyWord
-
- equals(Object) - Method in class org.deeplearning4j.nn.conf.distribution.BinomialDistribution
-
- equals(Object) - Method in class org.deeplearning4j.nn.conf.distribution.ConstantDistribution
-
- equals(Object) - Method in class org.deeplearning4j.nn.conf.distribution.LogNormalDistribution
-
- equals(Object) - Method in class org.deeplearning4j.nn.conf.distribution.NormalDistribution
-
- equals(Object) - Method in class org.deeplearning4j.nn.conf.distribution.OrthogonalDistribution
-
- equals(Object) - Method in class org.deeplearning4j.nn.conf.distribution.TruncatedNormalDistribution
-
- equals(Object) - Method in class org.deeplearning4j.nn.conf.distribution.UniformDistribution
-
- equals(Object) - Method in class org.deeplearning4j.nn.conf.graph.ElementWiseVertex
-
- equals(Object) - Method in class org.deeplearning4j.nn.conf.graph.GraphVertex
-
- equals(Object) - Method in class org.deeplearning4j.nn.conf.graph.L2NormalizeVertex
-
- equals(Object) - Method in class org.deeplearning4j.nn.conf.graph.L2Vertex
-
- equals(Object) - Method in class org.deeplearning4j.nn.conf.graph.LayerVertex
-
- equals(Object) - Method in class org.deeplearning4j.nn.conf.graph.MergeVertex
-
- equals(Object) - Method in class org.deeplearning4j.nn.conf.graph.PoolHelperVertex
-
- equals(Object) - Method in class org.deeplearning4j.nn.conf.graph.PreprocessorVertex
-
- equals(Object) - Method in class org.deeplearning4j.nn.conf.graph.ReshapeVertex
-
- equals(Object) - Method in class org.deeplearning4j.nn.conf.graph.rnn.DuplicateToTimeSeriesVertex
-
- equals(Object) - Method in class org.deeplearning4j.nn.conf.graph.rnn.LastTimeStepVertex
-
- equals(Object) - Method in class org.deeplearning4j.nn.conf.graph.rnn.ReverseTimeSeriesVertex
-
- equals(Object) - Method in class org.deeplearning4j.nn.conf.graph.ScaleVertex
-
- equals(Object) - Method in class org.deeplearning4j.nn.conf.graph.StackVertex
-
- equals(Object) - Method in class org.deeplearning4j.nn.conf.graph.SubsetVertex
-
- equals(Object) - Method in class org.deeplearning4j.nn.conf.graph.UnstackVertex
-
- equals(Object) - Method in class org.deeplearning4j.nn.conf.layers.samediff.SDLayerParams
-
- equals(Object) - Method in class org.deeplearning4j.nn.conf.stepfunctions.DefaultStepFunction
-
- equals(Object) - Method in class org.deeplearning4j.nn.conf.stepfunctions.GradientStepFunction
-
- equals(Object) - Method in class org.deeplearning4j.nn.conf.stepfunctions.NegativeDefaultStepFunction
-
- equals(Object) - Method in class org.deeplearning4j.nn.conf.stepfunctions.NegativeGradientStepFunction
-
- equals(Object) - Method in class org.deeplearning4j.nn.graph.ComputationGraph
-
Indicates whether some other object is "equal to" this one.
- equals(Object) - Method in class org.deeplearning4j.nn.layers.feedforward.autoencoder.recursive.Tree
-
- equals(Object) - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
-
Indicates whether some other object is "equal to" this one.
- equals(Object) - Method in class org.deeplearning4j.nn.updater.BaseMultiLayerUpdater
-
- equals(Object) - Method in class org.deeplearning4j.ui.nearestneighbors.word2vec.NearestNeighborsQuery
-
- equals(Object) - Method in class org.deeplearning4j.ui.weights.beans.CompactModelAndGradient
-
- equiv(DataSet, DataSet) - Method in class org.deeplearning4j.spark.ordering.DataSetOrdering
-
- error() - Method in class org.deeplearning4j.nn.layers.feedforward.autoencoder.recursive.Tree
-
Returns the prediction error for this node
- errorFor(double, double) - Static method in class org.deeplearning4j.clustering.util.MathUtils
-
- errorIfGraphIfMLN() - Method in class org.deeplearning4j.nn.transferlearning.TransferLearningHelper
-
- errorSum() - Method in class org.deeplearning4j.nn.layers.feedforward.autoencoder.recursive.Tree
-
Returns the total prediction error for this
tree and its children
- escape(String) - Static method in class com.atilika.kuromoji.util.DictionaryEntryLineParser
-
Escape input for CSV
- esConfig - Variable in class org.deeplearning4j.earlystopping.trainer.BaseEarlyStoppingTrainer
-
- esConfig - Variable in class org.deeplearning4j.parallelism.EarlyStoppingParallelTrainer
-
- EUCLIDEAN - Static variable in class org.deeplearning4j.clustering.vptree.VPTree
-
- euclideanDistance(double[], double[]) - Static method in class org.deeplearning4j.clustering.util.MathUtils
-
This returns the distance of two vectors
sum(i=1,n) (q_i - p_i)^2
- euclideanDistance(float[], float[]) - Static method in class org.deeplearning4j.clustering.util.MathUtils
-
This returns the distance of two vectors
sum(i=1,n) (q_i - p_i)^2
- eval(INDArray, INDArray, List<? extends Serializable>) - Method in class org.deeplearning4j.eval.BaseEvaluation
-
- eval(INDArray, INDArray, INDArray) - Method in class org.deeplearning4j.eval.BaseEvaluation
-
- eval(INDArray, INDArray, ComputationGraph) - Method in class org.deeplearning4j.eval.Evaluation
-
Evaluate the output
using the given true labels,
the input to the multi layer network
and the multi layer network to
use for evaluation
- eval(INDArray, INDArray, MultiLayerNetwork) - Method in class org.deeplearning4j.eval.Evaluation
-
Evaluate the output
using the given true labels,
the input to the multi layer network
and the multi layer network to
use for evaluation
- eval(INDArray, INDArray) - Method in class org.deeplearning4j.eval.Evaluation
-
Collects statistics on the real outcomes vs the
guesses.
- eval(INDArray, INDArray, List<? extends Serializable>) - Method in class org.deeplearning4j.eval.Evaluation
-
Evaluate the network, with optional metadata
- eval(int, int) - Method in class org.deeplearning4j.eval.Evaluation
-
Evaluate a single prediction (one prediction at a time)
- eval(INDArray, INDArray) - Method in class org.deeplearning4j.eval.EvaluationBinary
-
- eval(INDArray, INDArray, INDArray) - Method in class org.deeplearning4j.eval.EvaluationBinary
-
- eval(INDArray, INDArray, INDArray) - Method in class org.deeplearning4j.eval.EvaluationCalibration
-
- eval(INDArray, INDArray) - Method in class org.deeplearning4j.eval.EvaluationCalibration
-
- eval(INDArray, INDArray) - Method in interface org.deeplearning4j.eval.IEvaluation
-
- eval(INDArray, INDArray, List<? extends Serializable>) - Method in interface org.deeplearning4j.eval.IEvaluation
-
- eval(INDArray, INDArray, INDArray) - Method in interface org.deeplearning4j.eval.IEvaluation
-
- eval(INDArray, INDArray) - Method in class org.deeplearning4j.eval.RegressionEvaluation
-
- eval(INDArray, INDArray, INDArray) - Method in class org.deeplearning4j.eval.RegressionEvaluation
-
- eval(INDArray, INDArray) - Method in class org.deeplearning4j.eval.ROC
-
Evaluate (collect statistics for) the given minibatch of data.
- eval(INDArray, INDArray) - Method in class org.deeplearning4j.eval.ROCBinary
-
- eval(INDArray, INDArray, INDArray) - Method in class org.deeplearning4j.eval.ROCBinary
-
- eval(INDArray, INDArray) - Method in class org.deeplearning4j.eval.ROCMultiClass
-
Evaluate (collect statistics for) the given minibatch of data.
- evalAtIndex(IEvaluation, INDArray[], INDArray[], int) - Method in class org.deeplearning4j.optimize.listeners.EvaluativeListener
-
- evalTimeSeries(INDArray, INDArray) - Method in class org.deeplearning4j.eval.BaseEvaluation
-
- evalTimeSeries(INDArray, INDArray, INDArray) - Method in class org.deeplearning4j.eval.BaseEvaluation
-
- evalTimeSeries(INDArray, INDArray, INDArray) - Method in class org.deeplearning4j.eval.EvaluationBinary
-
- evalTimeSeries(INDArray, INDArray) - Method in interface org.deeplearning4j.eval.IEvaluation
-
- evalTimeSeries(INDArray, INDArray, INDArray) - Method in interface org.deeplearning4j.eval.IEvaluation
-
- evaluate(DataSetIterator) - Method in class org.deeplearning4j.nn.graph.ComputationGraph
-
Evaluate the network (classification performance - single output ComputationGraphs only)
- evaluate(MultiDataSetIterator) - Method in class org.deeplearning4j.nn.graph.ComputationGraph
-
Evaluate the network (classification performance - single output ComputationGraphs only)
- evaluate(DataSetIterator, List<String>) - Method in class org.deeplearning4j.nn.graph.ComputationGraph
-
Evaluate the network on the provided data set (single output ComputationGraphs only).
- evaluate(MultiDataSetIterator, List<String>) - Method in class org.deeplearning4j.nn.graph.ComputationGraph
-
Evaluate the network on the provided data set (single output ComputationGraphs only).
- evaluate(DataSetIterator, List<String>, int) - Method in class org.deeplearning4j.nn.graph.ComputationGraph
-
Evaluate the network (for classification) on the provided data set, with top N accuracy in addition to standard accuracy.
- evaluate(MultiDataSetIterator, List<String>, int) - Method in class org.deeplearning4j.nn.graph.ComputationGraph
-
Evaluate the network (for classification) on the provided data set, with top N accuracy in addition to standard accuracy.
- evaluate(DataSetIterator) - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
-
Evaluate the network (classification performance)
- evaluate(DataSetIterator, List<String>) - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
-
Evaluate the network on the provided data set.
- evaluate(DataSetIterator, List<String>, int) - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
-
Evaluate the network (for classification) on the provided data set, with top N accuracy in addition to standard accuracy.
- evaluate(RDD<DataSet>) - Method in class org.deeplearning4j.spark.impl.graph.SparkComputationGraph
-
- evaluate(JavaRDD<DataSet>) - Method in class org.deeplearning4j.spark.impl.graph.SparkComputationGraph
-
Evaluate the network (classification performance) in a distributed manner on the provided data
- evaluate(RDD<DataSet>, List<String>) - Method in class org.deeplearning4j.spark.impl.graph.SparkComputationGraph
-
- evaluate(JavaRDD<DataSet>, List<String>) - Method in class org.deeplearning4j.spark.impl.graph.SparkComputationGraph
-
Evaluate the network (classification performance) in a distributed manner, using default batch size and a provided
list of labels
- evaluate(JavaRDD<DataSet>, List<String>, int) - Method in class org.deeplearning4j.spark.impl.graph.SparkComputationGraph
-
Evaluate the network (classification performance) in a distributed manner, using specified batch size and a provided
list of labels
- evaluate(RDD<DataSet>) - Method in class org.deeplearning4j.spark.impl.multilayer.SparkDl4jMultiLayer
-
- evaluate(JavaRDD<DataSet>) - Method in class org.deeplearning4j.spark.impl.multilayer.SparkDl4jMultiLayer
-
Evaluate the network (classification performance) in a distributed manner on the provided data
- evaluate(RDD<DataSet>, List<String>) - Method in class org.deeplearning4j.spark.impl.multilayer.SparkDl4jMultiLayer
-
- evaluate(JavaRDD<DataSet>, List<String>) - Method in class org.deeplearning4j.spark.impl.multilayer.SparkDl4jMultiLayer
-
Evaluate the network (classification performance) in a distributed manner, using default batch size and a provided
list of labels
- evaluate(JavaRDD<DataSet>, List<String>, int) - Method in class org.deeplearning4j.spark.impl.multilayer.SparkDl4jMultiLayer
-
Evaluate the network (classification performance) in a distributed manner, using specified batch size and a provided
list of labels
- evaluateEveryNEpochs(int) - Method in class org.deeplearning4j.earlystopping.EarlyStoppingConfiguration.Builder
-
How frequently should evaluations be conducted (in terms of epochs)? Defaults to every (1) epochs.
- evaluateMDS(JavaRDD<MultiDataSet>) - Method in class org.deeplearning4j.spark.impl.graph.SparkComputationGraph
-
Evaluate the network (classification performance) in a distributed manner on the provided data
- evaluateMDS(JavaRDD<MultiDataSet>, int) - Method in class org.deeplearning4j.spark.impl.graph.SparkComputationGraph
-
Evaluate the network (classification performance) in a distributed manner on the provided data
- evaluateRegression(DataSetIterator) - Method in class org.deeplearning4j.nn.graph.ComputationGraph
-
Evaluate the (single output layer only) network for regression performance
- evaluateRegression(MultiDataSetIterator) - Method in class org.deeplearning4j.nn.graph.ComputationGraph
-
Evaluate the (single output layer only) network for regression performance
- evaluateRegression(DataSetIterator, List<String>) - Method in class org.deeplearning4j.nn.graph.ComputationGraph
-
Evaluate the (single output layer only) network for regression performance
- evaluateRegression(MultiDataSetIterator, List<String>) - Method in class org.deeplearning4j.nn.graph.ComputationGraph
-
Evaluate the (single output layer only) network for regression performance
- evaluateRegression(DataSetIterator) - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
-
Evaluate the network for regression performance
- evaluateRegression(JavaRDD<DataSet>) - Method in class org.deeplearning4j.spark.impl.graph.SparkComputationGraph
-
Evaluate the network (regression performance) in a distributed manner on the provided data
- evaluateRegression(JavaRDD<DataSet>, int) - Method in class org.deeplearning4j.spark.impl.graph.SparkComputationGraph
-
Evaluate the network (regression performance) in a distributed manner on the provided data
- evaluateRegression(JavaRDD<DataSet>) - Method in class org.deeplearning4j.spark.impl.multilayer.SparkDl4jMultiLayer
-
Evaluate the network (regression performance) in a distributed manner on the provided data
- evaluateRegression(JavaRDD<DataSet>, int) - Method in class org.deeplearning4j.spark.impl.multilayer.SparkDl4jMultiLayer
-
Evaluate the network (regression performance) in a distributed manner on the provided data
- evaluateRegressionMDS(JavaRDD<MultiDataSet>) - Method in class org.deeplearning4j.spark.impl.graph.SparkComputationGraph
-
Evaluate the network (regression performance) in a distributed manner on the provided data
- evaluateRegressionMDS(JavaRDD<MultiDataSet>, int) - Method in class org.deeplearning4j.spark.impl.graph.SparkComputationGraph
-
Evaluate the network (regression performance) in a distributed manner on the provided data
- evaluateROC(DataSetIterator) - Method in class org.deeplearning4j.nn.graph.ComputationGraph
-
Evaluate the network (must be a binary classifier) on the specified data, using the
ROC class.
- evaluateROC(DataSetIterator, int) - Method in class org.deeplearning4j.nn.graph.ComputationGraph
-
Evaluate the network (must be a binary classifier) on the specified data, using the
ROC class
- evaluateROC(MultiDataSetIterator) - Method in class org.deeplearning4j.nn.graph.ComputationGraph
-
Evaluate the network (must be a binary classifier) on the specified data, using the
ROC class.
- evaluateROC(MultiDataSetIterator, int) - Method in class org.deeplearning4j.nn.graph.ComputationGraph
-
Evaluate the network (must be a binary classifier) on the specified data, using the
ROC class
- evaluateROC(DataSetIterator) - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
-
Evaluate the network (must be a binary classifier) on the specified data, using the
ROC class.
- evaluateROC(DataSetIterator, int) - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
-
Evaluate the network (must be a binary classifier) on the specified data, using the
ROC class
- evaluateROC(JavaRDD<DataSet>) - Method in class org.deeplearning4j.spark.impl.graph.SparkComputationGraph
-
- evaluateROC(JavaRDD<DataSet>, int, int) - Method in class org.deeplearning4j.spark.impl.graph.SparkComputationGraph
-
Perform ROC analysis/evaluation on the given DataSet in a distributed manner
- evaluateROC(JavaRDD<DataSet>) - Method in class org.deeplearning4j.spark.impl.multilayer.SparkDl4jMultiLayer
-
- evaluateROC(JavaRDD<DataSet>, int, int) - Method in class org.deeplearning4j.spark.impl.multilayer.SparkDl4jMultiLayer
-
Perform ROC analysis/evaluation on the given DataSet in a distributed manner
- evaluateROCMDS(JavaRDD<MultiDataSet>) - Method in class org.deeplearning4j.spark.impl.graph.SparkComputationGraph
-
- evaluateROCMDS(JavaRDD<MultiDataSet>, int, int) - Method in class org.deeplearning4j.spark.impl.graph.SparkComputationGraph
-
Perform ROC analysis/evaluation on the given DataSet in a distributed manner, using the specified number of
steps and minibatch size
- evaluateROCMultiClass(DataSetIterator) - Method in class org.deeplearning4j.nn.graph.ComputationGraph
-
Evaluate the network on the specified data, using the
ROCMultiClass class.
- evaluateROCMultiClass(DataSetIterator, int) - Method in class org.deeplearning4j.nn.graph.ComputationGraph
-
Evaluate the network on the specified data, using the
ROCMultiClass class
- evaluateROCMultiClass(MultiDataSetIterator, int) - Method in class org.deeplearning4j.nn.graph.ComputationGraph
-
Evaluate the network on the specified data, using the
ROCMultiClass class
- evaluateROCMultiClass(DataSetIterator) - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
-
Evaluate the network on the specified data, using the
ROCMultiClass class.
- evaluateROCMultiClass(DataSetIterator, int) - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
-
Evaluate the network on the specified data, using the
ROCMultiClass class
- evaluateROCMultiClass(JavaRDD<DataSet>) - Method in class org.deeplearning4j.spark.impl.graph.SparkComputationGraph
-
Perform ROC analysis/evaluation (for the multi-class case, using
ROCMultiClass on the given DataSet in a distributed manner
- evaluateROCMultiClass(JavaRDD<DataSet>, int, int) - Method in class org.deeplearning4j.spark.impl.graph.SparkComputationGraph
-
Perform ROC analysis/evaluation (for the multi-class case, using
ROCMultiClass on the given DataSet in a distributed manner
- evaluateROCMultiClass(JavaRDD<DataSet>) - Method in class org.deeplearning4j.spark.impl.multilayer.SparkDl4jMultiLayer
-
Perform ROC analysis/evaluation (for the multi-class case, using
ROCMultiClass on the given DataSet in a distributed manner
- evaluateROCMultiClass(JavaRDD<DataSet>, int, int) - Method in class org.deeplearning4j.spark.impl.multilayer.SparkDl4jMultiLayer
-
Perform ROC analysis/evaluation (for the multi-class case, using
ROCMultiClass on the given DataSet in a distributed manner
- evaluation - Variable in class org.deeplearning4j.earlystopping.scorecalc.AutoencoderScoreCalculator
-
- evaluation - Variable in class org.deeplearning4j.earlystopping.scorecalc.VAEReconErrorScoreCalculator
-
- Evaluation - Class in org.deeplearning4j.eval
-
Evaluation metrics:
- precision, recall, f1, fBeta, accuracy, Matthews correlation coefficient, gMeasure
- Top N accuracy (if using constructor
Evaluation.Evaluation(List, int))
- Custom binary evaluation decision threshold (use constructor
Evaluation.Evaluation(double) (default if not set is
argmax / 0.5)
- Custom cost array, using
Evaluation.Evaluation(INDArray) or
Evaluation.Evaluation(List, INDArray) for multi-class
Note: Care should be taken when using the Evaluation class for binary classification metrics such as F1, precision,
recall, etc.
- Evaluation() - Constructor for class org.deeplearning4j.eval.Evaluation
-
- Evaluation(int) - Constructor for class org.deeplearning4j.eval.Evaluation
-
The number of classes to account for in the evaluation
- Evaluation(int, Integer) - Constructor for class org.deeplearning4j.eval.Evaluation
-
Constructor for specifying the number of classes, and optionally the positive class for binary classification.
- Evaluation(List<String>) - Constructor for class org.deeplearning4j.eval.Evaluation
-
The labels to include with the evaluation.
- Evaluation(Map<Integer, String>) - Constructor for class org.deeplearning4j.eval.Evaluation
-
Use a map to generate labels
Pass in a label index with the actual label
you want to use for output
- Evaluation(List<String>, int) - Constructor for class org.deeplearning4j.eval.Evaluation
-
Constructor to use for top N accuracy
- Evaluation(double) - Constructor for class org.deeplearning4j.eval.Evaluation
-
Create an evaluation instance with a custom binary decision threshold.
- Evaluation(double, Integer) - Constructor for class org.deeplearning4j.eval.Evaluation
-
Create an evaluation instance with a custom binary decision threshold.
- Evaluation(INDArray) - Constructor for class org.deeplearning4j.eval.Evaluation
-
Created evaluation instance with the specified cost array.
- Evaluation(List<String>, INDArray) - Constructor for class org.deeplearning4j.eval.Evaluation
-
Created evaluation instance with the specified cost array.
- Evaluation.Metric - Enum in org.deeplearning4j.eval
-
- EvaluationAveraging - Enum in org.deeplearning4j.eval
-
The averaging approach for binary valuation measures when applied to multiclass classification problems.
- EvaluationBinary - Class in org.deeplearning4j.eval
-
EvaluationBinary: used for evaluating networks with binary classification outputs.
- EvaluationBinary(INDArray) - Constructor for class org.deeplearning4j.eval.EvaluationBinary
-
Create an EvaulationBinary instance with an optional decision threshold array.
- EvaluationBinary(int, Integer) - Constructor for class org.deeplearning4j.eval.EvaluationBinary
-
This constructor allows for ROC to be calculated in addition to the standard evaluation metrics, when the
rocBinarySteps arg is non-null.
- EvaluationCalibration - Class in org.deeplearning4j.eval
-
EvaluationCalibration is an evaluation class designed to analyze the calibration of a classifier.
It provides a number of tools for this purpose:
- Counts of the number of labels and predictions for each class
- Reliability diagram (or reliability curve)
- Residual plot (histogram)
- Histograms of probabilities, including probabilities for each class separately
References:
- Reliability diagram: see for example Niculescu-Mizil and Caruana 2005, Predicting Good Probabilities With
Supervised Learning
- Residual plot: see Wallace and Dahabreh 2012, Class Probability Estimates are Unreliable for Imbalanced Data
(and How to Fix Them)
- EvaluationCalibration() - Constructor for class org.deeplearning4j.eval.EvaluationCalibration
-
Create an EvaluationCalibration instance with the default number of bins
- EvaluationCalibration(int, int) - Constructor for class org.deeplearning4j.eval.EvaluationCalibration
-
Create an EvaluationCalibration instance with the specified number of bins
- EvaluationCalibration(int, int, boolean) - Constructor for class org.deeplearning4j.eval.EvaluationCalibration
-
Create an EvaluationCalibration instance with the specified number of bins
- evaluationCalibrationToHtml(EvaluationCalibration) - Static method in class org.deeplearning4j.evaluation.EvaluationTools
-
- EvaluationCallback - Interface in org.deeplearning4j.optimize.listeners.callbacks
-
This interface describes callback, which can be used with EvaluativeListener, to extend its functionality.
- evaluations - Variable in class org.deeplearning4j.optimize.listeners.EvaluativeListener
-
- EvaluationTools - Class in org.deeplearning4j.evaluation
-
- EvaluationUtils - Class in org.deeplearning4j.eval
-
Utility methods for performing evaluation
- EvaluationUtils() - Constructor for class org.deeplearning4j.eval.EvaluationUtils
-
- EvaluativeListener - Class in org.deeplearning4j.optimize.listeners
-
This TrainingListener implementation provides simple way for model evaluation during training.
- EvaluativeListener(DataSetIterator, int) - Constructor for class org.deeplearning4j.optimize.listeners.EvaluativeListener
-
Evaluation will be launched after each *frequency* iteration
- EvaluativeListener(DataSetIterator, int, InvocationType) - Constructor for class org.deeplearning4j.optimize.listeners.EvaluativeListener
-
- EvaluativeListener(MultiDataSetIterator, int) - Constructor for class org.deeplearning4j.optimize.listeners.EvaluativeListener
-
Evaluation will be launched after each *frequency* iteration
- EvaluativeListener(MultiDataSetIterator, int, InvocationType) - Constructor for class org.deeplearning4j.optimize.listeners.EvaluativeListener
-
- EvaluativeListener(DataSetIterator, int, IEvaluation...) - Constructor for class org.deeplearning4j.optimize.listeners.EvaluativeListener
-
Evaluation will be launched after each *frequency* iteration
- EvaluativeListener(DataSetIterator, int, InvocationType, IEvaluation...) - Constructor for class org.deeplearning4j.optimize.listeners.EvaluativeListener
-
- EvaluativeListener(MultiDataSetIterator, int, IEvaluation...) - Constructor for class org.deeplearning4j.optimize.listeners.EvaluativeListener
-
Evaluation will be launched after each *frequency* iteration
- EvaluativeListener(MultiDataSetIterator, int, InvocationType, IEvaluation...) - Constructor for class org.deeplearning4j.optimize.listeners.EvaluativeListener
-
- EvaluativeListener(DataSet, int, InvocationType) - Constructor for class org.deeplearning4j.optimize.listeners.EvaluativeListener
-
- EvaluativeListener(MultiDataSet, int, InvocationType) - Constructor for class org.deeplearning4j.optimize.listeners.EvaluativeListener
-
- EvaluativeListener(DataSet, int, InvocationType, IEvaluation...) - Constructor for class org.deeplearning4j.optimize.listeners.EvaluativeListener
-
- EvaluativeListener(MultiDataSet, int, InvocationType, IEvaluation...) - Constructor for class org.deeplearning4j.optimize.listeners.EvaluativeListener
-
- eventListeners - Variable in class org.deeplearning4j.models.sequencevectors.SequenceVectors
-
- EventStats - Interface in org.deeplearning4j.spark.stats
-
Created by Alex on 26/06/2016.
- exampleCount - Variable in class org.deeplearning4j.datasets.iterator.impl.CifarDataSetIterator
-
- exampleCount - Variable in class org.deeplearning4j.earlystopping.scorecalc.base.BaseScoreCalculator
-
- ExampleCountEventStats - Class in org.deeplearning4j.spark.stats
-
Event stats implementation with number of examples
- ExampleCountEventStats(long, long, int) - Constructor for class org.deeplearning4j.spark.stats.ExampleCountEventStats
-
- ExampleCountEventStats(String, String, long, long, long, int) - Constructor for class org.deeplearning4j.spark.stats.ExampleCountEventStats
-
- exampleNegLogProbability(INDArray, INDArray) - Method in class org.deeplearning4j.nn.conf.layers.variational.BernoulliReconstructionDistribution
-
- exampleNegLogProbability(INDArray, INDArray) - Method in class org.deeplearning4j.nn.conf.layers.variational.CompositeReconstructionDistribution
-
- exampleNegLogProbability(INDArray, INDArray) - Method in class org.deeplearning4j.nn.conf.layers.variational.ExponentialReconstructionDistribution
-
- exampleNegLogProbability(INDArray, INDArray) - Method in class org.deeplearning4j.nn.conf.layers.variational.GaussianReconstructionDistribution
-
- exampleNegLogProbability(INDArray, INDArray) - Method in class org.deeplearning4j.nn.conf.layers.variational.LossFunctionWrapper
-
- exampleNegLogProbability(INDArray, INDArray) - Method in interface org.deeplearning4j.nn.conf.layers.variational.ReconstructionDistribution
-
Calculate the negative log probability for each example individually
- examplesPerSecond() - Method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder.PerformanceDecoder
-
- examplesPerSecond(float) - Method in class org.deeplearning4j.ui.stats.sbe.UpdateEncoder.PerformanceEncoder
-
- examplesPerSecondId() - Static method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder.PerformanceDecoder
-
- examplesPerSecondMaxValue() - Static method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder.PerformanceDecoder
-
- examplesPerSecondMaxValue() - Static method in class org.deeplearning4j.ui.stats.sbe.UpdateEncoder.PerformanceEncoder
-
- examplesPerSecondMetaAttribute(MetaAttribute) - Static method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder.PerformanceDecoder
-
- examplesPerSecondMinValue() - Static method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder.PerformanceDecoder
-
- examplesPerSecondMinValue() - Static method in class org.deeplearning4j.ui.stats.sbe.UpdateEncoder.PerformanceEncoder
-
- examplesPerSecondNullValue() - Static method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder.PerformanceDecoder
-
- examplesPerSecondNullValue() - Static method in class org.deeplearning4j.ui.stats.sbe.UpdateEncoder.PerformanceEncoder
-
- exception - Variable in class org.deeplearning4j.parallelism.inference.observers.BasicInferenceObservable
-
- exec() - Method in class org.deeplearning4j.aws.ec2.provision.ClusterSetup
-
- executeTraining(SparkDl4jMultiLayer, JavaRDD<DataSet>) - Method in interface org.deeplearning4j.spark.api.TrainingMaster
-
Train the SparkDl4jMultiLayer with the specified data set
- executeTraining(SparkDl4jMultiLayer, JavaPairRDD<String, PortableDataStream>) - Method in interface org.deeplearning4j.spark.api.TrainingMaster
-
- executeTraining(SparkComputationGraph, JavaRDD<DataSet>) - Method in interface org.deeplearning4j.spark.api.TrainingMaster
-
Train the SparkComputationGraph with the specified data set
- executeTraining(SparkComputationGraph, JavaPairRDD<String, PortableDataStream>) - Method in interface org.deeplearning4j.spark.api.TrainingMaster
-
- executeTraining(SparkDl4jMultiLayer, JavaRDD<DataSet>) - Method in class org.deeplearning4j.spark.impl.paramavg.ParameterAveragingTrainingMaster
-
- executeTraining(SparkDl4jMultiLayer, JavaPairRDD<String, PortableDataStream>) - Method in class org.deeplearning4j.spark.impl.paramavg.ParameterAveragingTrainingMaster
-
- executeTraining(SparkComputationGraph, JavaRDD<DataSet>) - Method in class org.deeplearning4j.spark.impl.paramavg.ParameterAveragingTrainingMaster
-
- executeTraining(SparkComputationGraph, JavaPairRDD<String, PortableDataStream>) - Method in class org.deeplearning4j.spark.impl.paramavg.ParameterAveragingTrainingMaster
-
- executeTraining(SparkDl4jMultiLayer, JavaRDD<DataSet>) - Method in class org.deeplearning4j.spark.parameterserver.training.SharedTrainingMaster
-
- executeTraining(SparkDl4jMultiLayer, JavaPairRDD<String, PortableDataStream>) - Method in class org.deeplearning4j.spark.parameterserver.training.SharedTrainingMaster
-
- executeTraining(SparkComputationGraph, JavaRDD<DataSet>) - Method in class org.deeplearning4j.spark.parameterserver.training.SharedTrainingMaster
-
- executeTraining(SparkComputationGraph, JavaPairRDD<String, PortableDataStream>) - Method in class org.deeplearning4j.spark.parameterserver.training.SharedTrainingMaster
-
- executeTrainingDirect(SparkDl4jMultiLayer, JavaRDD<DataSet>) - Method in class org.deeplearning4j.spark.impl.paramavg.ParameterAveragingTrainingMaster
-
- executeTrainingDirect(SparkComputationGraph, JavaRDD<MultiDataSet>) - Method in class org.deeplearning4j.spark.impl.paramavg.ParameterAveragingTrainingMaster
-
- executeTrainingDirect(SparkDl4jMultiLayer, JavaRDD<DataSet>) - Method in class org.deeplearning4j.spark.parameterserver.training.SharedTrainingMaster
-
- executeTrainingDirect(SparkComputationGraph, JavaRDD<DataSet>) - Method in class org.deeplearning4j.spark.parameterserver.training.SharedTrainingMaster
-
- executeTrainingDirectMDS(SparkComputationGraph, JavaRDD<MultiDataSet>) - Method in class org.deeplearning4j.spark.parameterserver.training.SharedTrainingMaster
-
- executeTrainingMDS(SparkComputationGraph, JavaRDD<MultiDataSet>) - Method in interface org.deeplearning4j.spark.api.TrainingMaster
-
Train the SparkComputationGraph with the specified data set
- executeTrainingMDS(SparkComputationGraph, JavaPairRDD<String, PortableDataStream>) - Method in interface org.deeplearning4j.spark.api.TrainingMaster
-
- executeTrainingMDS(SparkComputationGraph, JavaRDD<MultiDataSet>) - Method in class org.deeplearning4j.spark.impl.paramavg.ParameterAveragingTrainingMaster
-
- executeTrainingMDS(SparkComputationGraph, JavaPairRDD<String, PortableDataStream>) - Method in class org.deeplearning4j.spark.impl.paramavg.ParameterAveragingTrainingMaster
-
- executeTrainingMDS(SparkComputationGraph, JavaRDD<MultiDataSet>) - Method in class org.deeplearning4j.spark.parameterserver.training.SharedTrainingMaster
-
- executeTrainingMDS(SparkComputationGraph, JavaPairRDD<String, PortableDataStream>) - Method in class org.deeplearning4j.spark.parameterserver.training.SharedTrainingMaster
-
- executeTrainingPaths(SparkDl4jMultiLayer, JavaRDD<String>) - Method in interface org.deeplearning4j.spark.api.TrainingMaster
-
EXPERIMENTAL method, may be removed in a future release.
Fit the network using a list of paths for serialized DataSet objects.
- executeTrainingPaths(SparkComputationGraph, JavaRDD<String>) - Method in interface org.deeplearning4j.spark.api.TrainingMaster
-
EXPERIMENTAL method, may be removed in a future release.
Fit the network using a list of paths for serialized DataSet objects.
- executeTrainingPaths(SparkDl4jMultiLayer, JavaRDD<String>) - Method in class org.deeplearning4j.spark.impl.paramavg.ParameterAveragingTrainingMaster
-
- executeTrainingPaths(SparkComputationGraph, JavaRDD<String>) - Method in class org.deeplearning4j.spark.impl.paramavg.ParameterAveragingTrainingMaster
-
- executeTrainingPaths(SparkDl4jMultiLayer, JavaRDD<String>) - Method in class org.deeplearning4j.spark.parameterserver.training.SharedTrainingMaster
-
- executeTrainingPaths(SparkComputationGraph, JavaRDD<String>) - Method in class org.deeplearning4j.spark.parameterserver.training.SharedTrainingMaster
-
- executeTrainingPathsHelper(SparkDl4jMultiLayer, JavaRDD<String>, int) - Method in class org.deeplearning4j.spark.impl.paramavg.ParameterAveragingTrainingMaster
-
- executeTrainingPathsHelper(SparkDl4jMultiLayer, JavaRDD<String>, int) - Method in class org.deeplearning4j.spark.parameterserver.training.SharedTrainingMaster
-
- executeTrainingPathsHelper(SparkComputationGraph, JavaRDD<String>, int) - Method in class org.deeplearning4j.spark.parameterserver.training.SharedTrainingMaster
-
- executeTrainingPathsMDS(SparkComputationGraph, JavaRDD<String>) - Method in interface org.deeplearning4j.spark.api.TrainingMaster
-
EXPERIMENTAL method, may be removed in a future release.
Fit the network using a list of paths for serialized MultiDataSet objects.
- executeTrainingPathsMDS(SparkComputationGraph, JavaRDD<String>) - Method in class org.deeplearning4j.spark.impl.paramavg.ParameterAveragingTrainingMaster
-
- executeTrainingPathsMDS(SparkComputationGraph, JavaRDD<String>) - Method in class org.deeplearning4j.spark.parameterserver.training.SharedTrainingMaster
-
- executeTrainingPathsMDSHelper(SparkComputationGraph, JavaRDD<String>, int) - Method in class org.deeplearning4j.spark.impl.paramavg.ParameterAveragingTrainingMaster
-
- executeTrainingPathsMDSHelper(SparkComputationGraph, JavaRDD<String>, int) - Method in class org.deeplearning4j.spark.parameterserver.training.SharedTrainingMaster
-
- ExecuteWorkerFlatMap<R extends TrainingResult> - Class in org.deeplearning4j.spark.api.worker
-
A FlatMapFunction for executing training on DataSets.
- ExecuteWorkerFlatMap(TrainingWorker<R>) - Constructor for class org.deeplearning4j.spark.api.worker.ExecuteWorkerFlatMap
-
- ExecuteWorkerMultiDataSetFlatMap<R extends TrainingResult> - Class in org.deeplearning4j.spark.api.worker
-
A FlatMapFunction for executing training on MultiDataSets.
- ExecuteWorkerMultiDataSetFlatMap(TrainingWorker<R>) - Constructor for class org.deeplearning4j.spark.api.worker.ExecuteWorkerMultiDataSetFlatMap
-
- ExecuteWorkerPathFlatMap<R extends TrainingResult> - Class in org.deeplearning4j.spark.api.worker
-
A FlatMapFunction for executing training on serialized DataSet objects, that can be loaded from a path (local or HDFS)
that is specified as a String
Used in both SparkDl4jMultiLayer and SparkComputationGraph implementations
- ExecuteWorkerPathFlatMap(TrainingWorker<R>) - Constructor for class org.deeplearning4j.spark.api.worker.ExecuteWorkerPathFlatMap
-
- ExecuteWorkerPathMDSFlatMap<R extends TrainingResult> - Class in org.deeplearning4j.spark.api.worker
-
A FlatMapFunction for executing training on serialized DataSet objects, that can be loaded from a path (local or HDFS)
that is specified as a String
Used in both SparkDl4jMultiLayer and SparkComputationGraph implementations
- ExecuteWorkerPathMDSFlatMap(TrainingWorker<R>) - Constructor for class org.deeplearning4j.spark.api.worker.ExecuteWorkerPathMDSFlatMap
-
- ExecuteWorkerPDSFlatMap<R extends TrainingResult> - Class in org.deeplearning4j.spark.api.worker
-
A FlatMapFunction for executing training on serialized DataSet objects, that can be loaded using a PortableDataStream
Used in both SparkDl4jMultiLayer and SparkComputationGraph implementations
- ExecuteWorkerPDSFlatMap(TrainingWorker<R>) - Constructor for class org.deeplearning4j.spark.api.worker.ExecuteWorkerPDSFlatMap
-
- ExecuteWorkerPDSMDSFlatMap<R extends TrainingResult> - Class in org.deeplearning4j.spark.api.worker
-
A FlatMapFunction for executing training on serialized MultiDataSet objects, that can be loaded using a PortableDataStream
Used for SparkComputationGraph implementations only
- ExecuteWorkerPDSMDSFlatMap(TrainingWorker<R>) - Constructor for class org.deeplearning4j.spark.api.worker.ExecuteWorkerPDSMDSFlatMap
-
- executorService - Variable in class org.deeplearning4j.parallelism.ParallelWrapper
-
- ExistingDataSetIterator - Class in org.deeplearning4j.datasets.iterator
-
This wrapper provides DataSetIterator interface to existing java Iterable and Iterator
- ExistingDataSetIterator(Iterator<DataSet>) - Constructor for class org.deeplearning4j.datasets.iterator.ExistingDataSetIterator
-
- ExistingDataSetIterator(Iterator<DataSet>, List<String>) - Constructor for class org.deeplearning4j.datasets.iterator.ExistingDataSetIterator
-
- ExistingDataSetIterator(Iterable<DataSet>) - Constructor for class org.deeplearning4j.datasets.iterator.ExistingDataSetIterator
-
- ExistingDataSetIterator(Iterable<DataSet>, List<String>) - Constructor for class org.deeplearning4j.datasets.iterator.ExistingDataSetIterator
-
- ExistingDataSetIterator(Iterable<DataSet>, int, int, int) - Constructor for class org.deeplearning4j.datasets.iterator.ExistingDataSetIterator
-
- existingModel - Variable in class org.deeplearning4j.models.sequencevectors.SequenceVectors
-
- existingVectors - Variable in class org.deeplearning4j.models.sequencevectors.SequenceVectors.Builder
-
- EXISTS - Static variable in class org.deeplearning4j.models.embeddings.reader.impl.BasicModelUtils
-
- expectedChecksum() - Method in class org.deeplearning4j.datasets.fetchers.CacheableExtractableDataSetFetcher
-
- expectedChecksum(DataSetType) - Method in class org.deeplearning4j.datasets.fetchers.SvhnDataFetcher
-
- expectedChecksum(DataSetType) - Method in class org.deeplearning4j.datasets.fetchers.TinyImageNetFetcher
-
- expectedChecksum() - Method in class org.deeplearning4j.datasets.fetchers.UciSequenceDataFetcher
-
- expectedChecksum(DataSetType) - Method in class org.deeplearning4j.datasets.fetchers.UciSequenceDataFetcher
-
- explain(LeafReaderContext, int, float, List<Explanation>) - Method in class org.deeplearning4j.nn.modelexport.solr.ltr.model.ScoringModel
-
- ExponentialReconstructionDistribution - Class in org.deeplearning4j.nn.conf.layers.variational
-
Exponential reconstruction distribution.
Supports data in range [0,infinity)
- ExponentialReconstructionDistribution() - Constructor for class org.deeplearning4j.nn.conf.layers.variational.ExponentialReconstructionDistribution
-
- ExponentialReconstructionDistribution(String) - Constructor for class org.deeplearning4j.nn.conf.layers.variational.ExponentialReconstructionDistribution
-
- ExponentialReconstructionDistribution(Activation) - Constructor for class org.deeplearning4j.nn.conf.layers.variational.ExponentialReconstructionDistribution
-
- ExponentialReconstructionDistribution(IActivation) - Constructor for class org.deeplearning4j.nn.conf.layers.variational.ExponentialReconstructionDistribution
-
- export(JavaRDD<DataSet>) - Method in class org.deeplearning4j.spark.impl.paramavg.BaseTrainingMaster
-
- export(JavaRDD<ExportContainer<T>>) - Method in class org.deeplearning4j.spark.models.sequencevectors.export.impl.HdfsModelExporter
-
- export(JavaRDD<ExportContainer<VocabWord>>) - Method in class org.deeplearning4j.spark.models.sequencevectors.export.impl.VocabCacheExporter
-
- export(JavaRDD<ExportContainer<T>>) - Method in interface org.deeplearning4j.spark.models.sequencevectors.export.SparkModelExporter
-
This method will be called at final stage of SequenceVectors training, and JavaRDD being passed as argument will
- ExportContainer<T extends SequenceElement> - Class in org.deeplearning4j.spark.models.sequencevectors.export
-
- ExportContainer() - Constructor for class org.deeplearning4j.spark.models.sequencevectors.export.ExportContainer
-
- exportDirectory - Variable in class org.deeplearning4j.spark.impl.paramavg.BaseTrainingMaster
-
- exportDirectory - Variable in class org.deeplearning4j.spark.impl.paramavg.ParameterAveragingTrainingMaster.Builder
-
- exportDirectory(String) - Method in class org.deeplearning4j.spark.impl.paramavg.ParameterAveragingTrainingMaster.Builder
-
- exportDirectory - Variable in class org.deeplearning4j.spark.parameterserver.training.SharedTrainingMaster.Builder
-
- exportDirectory(String) - Method in class org.deeplearning4j.spark.parameterserver.training.SharedTrainingMaster.Builder
-
- exporter - Variable in class org.deeplearning4j.spark.models.sequencevectors.SparkSequenceVectors
-
- exportevaluationCalibrationToHtmlFile(EvaluationCalibration, File) - Static method in class org.deeplearning4j.evaluation.EvaluationTools
-
- ExportFunction<T extends SequenceElement> - Class in org.deeplearning4j.spark.models.sequencevectors.functions
-
This function is used to
- ExportFunction(Broadcast<VocabCache<ShallowSequenceElement>>, String) - Constructor for class org.deeplearning4j.spark.models.sequencevectors.functions.ExportFunction
-
- exportIfRequired(JavaSparkContext, JavaRDD<DataSet>) - Method in class org.deeplearning4j.spark.impl.paramavg.BaseTrainingMaster
-
- exportIfRequiredMDS(JavaSparkContext, JavaRDD<MultiDataSet>) - Method in class org.deeplearning4j.spark.impl.paramavg.BaseTrainingMaster
-
- exportMDS(JavaRDD<MultiDataSet>) - Method in class org.deeplearning4j.spark.impl.paramavg.BaseTrainingMaster
-
- exportRocChartsToHtmlFile(ROC, File) - Static method in class org.deeplearning4j.evaluation.EvaluationTools
-
Given a
ROC chart, export the ROC chart and precision vs.
- exportRocChartsToHtmlFile(ROCMultiClass, File) - Static method in class org.deeplearning4j.evaluation.EvaluationTools
-
Given a
ROCMultiClass chart, export the ROC chart and precision vs.
- exportScores(OutputStream) - Method in class org.deeplearning4j.optimize.listeners.CollectScoresIterationListener
-
Export the scores in tab-delimited (one per line) UTF-8 format.
- exportScores(OutputStream, String) - Method in class org.deeplearning4j.optimize.listeners.CollectScoresIterationListener
-
Export the scores in delimited (one per line) UTF-8 format with the specified delimiter
- exportScores(File) - Method in class org.deeplearning4j.optimize.listeners.CollectScoresIterationListener
-
Export the scores to the specified file in delimited (one per line) UTF-8 format, tab delimited
- exportScores(File, String) - Method in class org.deeplearning4j.optimize.listeners.CollectScoresIterationListener
-
Export the scores to the specified file in delimited (one per line) UTF-8 format, using the specified delimiter
- exportStatFiles(String, SparkContext) - Method in class org.deeplearning4j.spark.api.stats.CommonSparkTrainingStats
-
- exportStatFiles(String, SparkContext) - Method in interface org.deeplearning4j.spark.api.stats.SparkTrainingStats
-
Export the stats as a collection of files.
- exportStatFiles(String, SparkContext) - Method in class org.deeplearning4j.spark.impl.paramavg.stats.ParameterAveragingTrainingMasterStats
-
- exportStatFiles(String, SparkContext) - Method in class org.deeplearning4j.spark.impl.paramavg.stats.ParameterAveragingTrainingWorkerStats
-
- exportStats(List<EventStats>, String, String, String, SparkContext) - Static method in class org.deeplearning4j.spark.stats.StatsUtils
-
- exportStats(List<EventStats>, String, String, SparkContext) - Static method in class org.deeplearning4j.spark.stats.StatsUtils
-
- exportStatsAsHtml(SparkTrainingStats, String, JavaSparkContext) - Static method in class org.deeplearning4j.spark.stats.StatsUtils
-
- exportStatsAsHtml(SparkTrainingStats, String, SparkContext) - Static method in class org.deeplearning4j.spark.stats.StatsUtils
-
Generate and export a HTML representation (including charts, etc) of the Spark training statistics
Note: exporting is done via Spark, so the path here can be a local file, HDFS, etc.
- exportStatsAsHtml(SparkTrainingStats, long, String, SparkContext) - Static method in class org.deeplearning4j.spark.stats.StatsUtils
-
Generate and export a HTML representation (including charts, etc) of the Spark training statistics
Note: exporting is done via Spark, so the path here can be a local file, HDFS, etc.
- exportStatsAsHTML(SparkTrainingStats, OutputStream) - Static method in class org.deeplearning4j.spark.stats.StatsUtils
-
Generate and export a HTML representation (including charts, etc) of the Spark training statistics
This overload is for writing to an output stream
- exportStatsAsHTML(SparkTrainingStats, long, OutputStream) - Static method in class org.deeplearning4j.spark.stats.StatsUtils
-
Generate and export a HTML representation (including charts, etc) of the Spark training statistics
This overload is for writing to an output stream
- ExportSupport - Class in org.deeplearning4j.spark.impl.paramavg.util
-
Utility for checking if exporting data sets is supported
- ExportSupport() - Constructor for class org.deeplearning4j.spark.impl.paramavg.util.ExportSupport
-
- exportSupported(JavaSparkContext) - Static method in class org.deeplearning4j.spark.impl.paramavg.util.ExportSupport
-
Check if exporting data is supported in the current environment.
- exportSupported(String, FileSystem) - Static method in class org.deeplearning4j.spark.impl.paramavg.util.ExportSupport
-
Check if exporting data is supported in the current environment.
- expTable - Variable in class org.deeplearning4j.graph.models.embeddings.InMemoryGraphLookupTable
-
- expTable - Variable in class org.deeplearning4j.models.embeddings.inmemory.InMemoryLookupTable
-
- expTable - Variable in class org.deeplearning4j.models.embeddings.learning.impl.elements.CBOW
-
- expTable - Variable in class org.deeplearning4j.models.embeddings.learning.impl.elements.SkipGram
-
- expTable - Variable in class org.deeplearning4j.models.embeddings.learning.impl.sequence.DM
-
- expTable(Broadcast<double[]>) - Method in class org.deeplearning4j.spark.models.embeddings.word2vec.Word2VecParam.Builder
-
Deprecated.
- extCounter - Variable in class org.deeplearning4j.optimize.solvers.accumulation.BasicGradientsAccumulator
-
- externalCache(VocabCache) - Method in class org.deeplearning4j.models.word2vec.wordstore.VocabularyHolder.Builder
-
- externalCall() - Method in class org.deeplearning4j.datasets.iterator.AsyncDataSetIterator
-
- externalCall() - Method in class org.deeplearning4j.datasets.iterator.AsyncMultiDataSetIterator
-
- externalCall() - Method in class org.deeplearning4j.spark.iterator.SparkADSI
-
- externalCall() - Method in class org.deeplearning4j.spark.iterator.SparkAMDSI
-
- externalSource - Variable in class org.deeplearning4j.optimize.solvers.accumulation.EncodedGradientsAccumulator
-
- ExtraCounter<E> - Class in org.deeplearning4j.spark.models.sequencevectors.primitives
-
This class serves as Counter for SparkSequenceVectors vocab creation + for distributed parameters server organization
Ip addresses extracted here will be used for ParamServer shards selection, and won't be used for anything else
- ExtraCounter() - Constructor for class org.deeplearning4j.spark.models.sequencevectors.primitives.ExtraCounter
-
- ExtraCountFunction<T extends SequenceElement> - Class in org.deeplearning4j.spark.models.sequencevectors.functions
-
This accumulator function does count individual elements, using provided Accumulator
- ExtraCountFunction(Accumulator<ExtraCounter<Long>>, boolean) - Constructor for class org.deeplearning4j.spark.models.sequencevectors.functions.ExtraCountFunction
-
- extract(String) - Method in class org.deeplearning4j.text.corpora.sentiwordnet.SWN3
-
- extractLabels() - Method in class org.deeplearning4j.models.paragraphvectors.ParagraphVectors
-
- extractNonMaskedTimeSteps(INDArray, INDArray, INDArray) - Static method in class org.deeplearning4j.eval.EvaluationUtils
-
- extractOtherFeatures(DictionaryEntry) - Method in class com.atilika.kuromoji.ipadic.compile.TokenInfoDictionaryCompiler
-
- extractPosFeatures(DictionaryEntry) - Method in class com.atilika.kuromoji.ipadic.compile.TokenInfoDictionaryCompiler
-
- ExtraElementsFrequenciesAccumulator - Class in org.deeplearning4j.spark.models.sequencevectors.functions
-
Accumulator for elements count
- ExtraElementsFrequenciesAccumulator() - Constructor for class org.deeplearning4j.spark.models.sequencevectors.functions.ExtraElementsFrequenciesAccumulator
-
- extraMetaDataBytes() - Method in class org.deeplearning4j.ui.stats.sbe.StorageMetaDataDecoder
-
- extraMetaDataBytesCount(int) - Method in class org.deeplearning4j.ui.stats.sbe.StorageMetaDataEncoder
-
- ExtraMetaDataBytesDecoder() - Constructor for class org.deeplearning4j.ui.stats.sbe.StorageMetaDataDecoder.ExtraMetaDataBytesDecoder
-
- extraMetaDataBytesDecoderId() - Static method in class org.deeplearning4j.ui.stats.sbe.StorageMetaDataDecoder
-
- ExtraMetaDataBytesEncoder() - Constructor for class org.deeplearning4j.ui.stats.sbe.StorageMetaDataEncoder.ExtraMetaDataBytesEncoder
-
- extraMetaDataBytesId() - Static method in class org.deeplearning4j.ui.stats.sbe.StorageMetaDataEncoder
-
- f1(int) - Method in class org.deeplearning4j.eval.Evaluation
-
Calculate f1 score for a given class
- f1() - Method in class org.deeplearning4j.eval.Evaluation
-
Calculate the F1 score
F1 score is defined as:
TP: true positive
FP: False Positive
FN: False Negative
F1 score: 2 * TP / (2TP + FP + FN)
Note: value returned will differ depending on number of classes and settings.
1.
- f1(EvaluationAveraging) - Method in class org.deeplearning4j.eval.Evaluation
-
Calculate the average F1 score across all classes, using macro or micro averaging
- f1(int) - Method in class org.deeplearning4j.eval.EvaluationBinary
-
Get the F1 score for the specified output
- f1Score(DataSet) - Method in interface org.deeplearning4j.nn.api.Classifier
-
Sets the input and labels and returns a score for the prediction
wrt true labels
- f1Score(INDArray, INDArray) - Method in interface org.deeplearning4j.nn.api.Classifier
-
Returns the f1 score for the given examples.
- f1Score(DataSet) - Method in class org.deeplearning4j.nn.layers.BaseOutputLayer
-
Sets the input and labels and returns a score for the prediction
wrt true labels
- f1Score(INDArray, INDArray) - Method in class org.deeplearning4j.nn.layers.BaseOutputLayer
-
Returns the f1 score for the given examples.
- f1Score(DataSet) - Method in class org.deeplearning4j.nn.layers.convolution.CnnLossLayer
-
- f1Score(INDArray, INDArray) - Method in class org.deeplearning4j.nn.layers.convolution.CnnLossLayer
-
Returns the f1 score for the given examples.
- f1Score(DataSet) - Method in class org.deeplearning4j.nn.layers.LossLayer
-
Sets the input and labels and returns a score for the prediction
wrt true labels
- f1Score(INDArray, INDArray) - Method in class org.deeplearning4j.nn.layers.LossLayer
-
Returns the f1 score for the given examples.
- f1Score(DataSet) - Method in class org.deeplearning4j.nn.layers.objdetect.Yolo2OutputLayer
-
- f1Score(INDArray, INDArray) - Method in class org.deeplearning4j.nn.layers.objdetect.Yolo2OutputLayer
-
- f1Score(INDArray, INDArray) - Method in class org.deeplearning4j.nn.layers.ocnn.OCNNOutputLayer
-
Returns the f1 score for the given examples.
- f1Score(DataSet) - Method in class org.deeplearning4j.nn.layers.recurrent.RnnLossLayer
-
- f1Score(INDArray, INDArray) - Method in class org.deeplearning4j.nn.layers.recurrent.RnnLossLayer
-
Returns the f1 score for the given examples.
- f1Score(INDArray, INDArray) - Method in class org.deeplearning4j.nn.layers.recurrent.RnnOutputLayer
-
Returns the f1 score for the given examples.
- f1Score(DataSet) - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
-
Sets the input and labels and returns a score for the prediction
wrt true labels
- f1Score(INDArray, INDArray) - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
-
Sets the input and labels and returns a score for the prediction
wrt true labels
- fa - Variable in class org.deeplearning4j.nn.layers.recurrent.FwdPassReturn
-
- FaceNetHelper - Class in org.deeplearning4j.zoo.model.helper
-
Inception is based on GoogleLeNet configuration of convolutional layers for optimization of
resources and learning.
- FaceNetHelper() - Constructor for class org.deeplearning4j.zoo.model.helper.FaceNetHelper
-
- FaceNetNN4Small2 - Class in org.deeplearning4j.zoo.model
-
A variant of the original FaceNet model that relies on embeddings and triplet loss.
- factorial(double) - Static method in class org.deeplearning4j.clustering.util.MathUtils
-
This will return the factorial of the given number n.
- FALLBACK_LANGUAGE - Static variable in class org.deeplearning4j.ui.i18n.DefaultI18N
-
- fallbackToSingleConsumerMode(boolean) - Method in class org.deeplearning4j.optimize.solvers.accumulation.EncodedGradientsAccumulator
-
- fallbackToSingleConsumerMode(boolean) - Method in class org.deeplearning4j.optimize.solvers.accumulation.FancyBlockingQueue
-
- fallbackToSingleConsumerMode(boolean) - Method in interface org.deeplearning4j.optimize.solvers.accumulation.Registerable
-
This method enables/disables bypass mode
- falseAlarmRate() - Method in class org.deeplearning4j.eval.Evaluation
-
False Alarm Rate (FAR) reflects rate of misclassified to classified records
http://ro.ecu.edu.au/cgi/viewcontent.cgi?article=1058&context=isw
Note: value returned will differ depending on number of classes and settings.
1.
- falseNegativeRate(Integer) - Method in class org.deeplearning4j.eval.Evaluation
-
Returns the false negative rate for a given label
- falseNegativeRate(Integer, double) - Method in class org.deeplearning4j.eval.Evaluation
-
Returns the false negative rate for a given label
- falseNegativeRate() - Method in class org.deeplearning4j.eval.Evaluation
-
False negative rate based on guesses so far
Note: value returned will differ depending on number of classes and settings.
1.
- falseNegativeRate(EvaluationAveraging) - Method in class org.deeplearning4j.eval.Evaluation
-
Calculate the average false negative rate for all classes - can specify whether macro or micro averaging should be used
- falseNegativeRate(Integer) - Method in class org.deeplearning4j.eval.EvaluationBinary
-
Returns the false negative rate for a given label
- falseNegativeRate(Integer, double) - Method in class org.deeplearning4j.eval.EvaluationBinary
-
Returns the false negative rate for a given label
- falseNegativeRate(long, long, double) - Static method in class org.deeplearning4j.eval.EvaluationUtils
-
Calculate the false negative rate from the false negative counts and true positive count
- falseNegatives - Variable in class org.deeplearning4j.eval.Evaluation
-
- falseNegatives() - Method in class org.deeplearning4j.eval.Evaluation
-
False negatives: correctly rejected
- falseNegatives(int) - Method in class org.deeplearning4j.eval.EvaluationBinary
-
Get the false negatives count for the specified output
- falsePositiveRate(int) - Method in class org.deeplearning4j.eval.Evaluation
-
Returns the false positive rate for a given label
- falsePositiveRate(int, double) - Method in class org.deeplearning4j.eval.Evaluation
-
Returns the false positive rate for a given label
- falsePositiveRate() - Method in class org.deeplearning4j.eval.Evaluation
-
False positive rate based on guesses so far
Note: value returned will differ depending on number of classes and settings.
1.
- falsePositiveRate(EvaluationAveraging) - Method in class org.deeplearning4j.eval.Evaluation
-
Calculate the average false positive rate across all classes.
- falsePositiveRate(int) - Method in class org.deeplearning4j.eval.EvaluationBinary
-
Returns the false positive rate for a given label
- falsePositiveRate(int, double) - Method in class org.deeplearning4j.eval.EvaluationBinary
-
Returns the false positive rate for a given label
- falsePositiveRate(long, long, double) - Static method in class org.deeplearning4j.eval.EvaluationUtils
-
Calculate the false positive rate from the false positive count and true negative count
- falsePositives - Variable in class org.deeplearning4j.eval.Evaluation
-
- falsePositives() - Method in class org.deeplearning4j.eval.Evaluation
-
False positive: wrong guess
- falsePositives(int) - Method in class org.deeplearning4j.eval.EvaluationBinary
-
Get the false positives count for the specified output
- FancyBlockingQueue<E> - Class in org.deeplearning4j.optimize.solvers.accumulation
-
This BlockingQueue implementation is suited only for symmetric gradients updates, and should NOT be used anywhere else.
- FancyBlockingQueue(BlockingQueue<E>) - Constructor for class org.deeplearning4j.optimize.solvers.accumulation.FancyBlockingQueue
-
- FancyBlockingQueue(BlockingQueue<E>, int) - Constructor for class org.deeplearning4j.optimize.solvers.accumulation.FancyBlockingQueue
-
- fBeta(double, int) - Method in class org.deeplearning4j.eval.Evaluation
-
Calculate the f_beta for a given class, where f_beta is defined as:
(1+beta^2) * (precision * recall) / (beta^2 * precision + recall).
F1 is a special case of f_beta, with beta=1.0
- fBeta(double, int, double) - Method in class org.deeplearning4j.eval.Evaluation
-
Calculate the f_beta for a given class, where f_beta is defined as:
(1+beta^2) * (precision * recall) / (beta^2 * precision + recall).
F1 is a special case of f_beta, with beta=1.0
- fBeta(double, EvaluationAveraging) - Method in class org.deeplearning4j.eval.Evaluation
-
Calculate the average F_beta score across all classes, using macro or micro averaging
- fBeta(double, int) - Method in class org.deeplearning4j.eval.EvaluationBinary
-
Calculate the F-beta value for the given output
- fBeta(double, long, long, long) - Static method in class org.deeplearning4j.eval.EvaluationUtils
-
Calculate the F beta value from counts
- fBeta(double, double, double) - Static method in class org.deeplearning4j.eval.EvaluationUtils
-
Calculate the F-beta value from precision and recall
- FEATURE_BEGIN - Static variable in class org.ansj.app.crf.Config
-
- FEATURE_MAP_FILENAME - Static variable in class com.atilika.kuromoji.dict.TokenInfoDictionary
-
- FeatureInfoMap - Class in com.atilika.kuromoji.buffer
-
- FeatureInfoMap() - Constructor for class com.atilika.kuromoji.buffer.FeatureInfoMap
-
- featureInfos - Variable in class com.atilika.kuromoji.buffer.BufferEntry
-
- features - Variable in class com.atilika.kuromoji.buffer.BufferEntry
-
- features(List<String>) - Method in class com.atilika.kuromoji.dict.GenericDictionaryEntry.Builder
-
- featureTree - Variable in class org.ansj.app.crf.Model
-
- featurize(MultiDataSet) - Method in class org.deeplearning4j.nn.transferlearning.TransferLearningHelper
-
During training frozen vertices/layers can be treated as "featurizing" the input
The forward pass through these frozen layer/vertices can be done in advance and the dataset saved to disk to iterate
quickly on the smaller unfrozen part of the model
Currently does not support datasets with feature masks
- featurize(DataSet) - Method in class org.deeplearning4j.nn.transferlearning.TransferLearningHelper
-
During training frozen vertices/layers can be treated as "featurizing" the input
The forward pass through these frozen layer/vertices can be done in advance and the dataset saved to disk to iterate
quickly on the smaller unfrozen part of the model
Currently does not support datasets with feature masks
- feedDataSet(DataSet, long) - Method in class org.deeplearning4j.parallelism.parameterserver.ParameterServerTrainer
-
- feedDataSet(DataSet, long) - Method in class org.deeplearning4j.parallelism.trainer.DefaultTrainer
-
- feedDataSet(DataSet, long) - Method in interface org.deeplearning4j.parallelism.trainer.Trainer
-
Train on a DataSet
- feedForward(int) - Static method in class org.deeplearning4j.nn.conf.inputs.InputType
-
InputType for feed forward network data
- feedForward(int) - Method in class org.deeplearning4j.nn.conf.NeuralNetConfiguration.ListBuilder.InputTypeBuilder
-
- feedForward(INDArray, int, boolean) - Method in class org.deeplearning4j.nn.graph.ComputationGraph
-
Conduct forward pass using a single input array.
- feedForward(INDArray[], int, boolean, boolean) - Method in class org.deeplearning4j.nn.graph.ComputationGraph
-
Conduct forward pass using an array of inputs.
- feedForward(INDArray[], int, boolean) - Method in class org.deeplearning4j.nn.graph.ComputationGraph
-
Conduct forward pass using an array of inputs
- feedForward(boolean, int) - Method in class org.deeplearning4j.nn.graph.ComputationGraph
-
Conduct forward pass using the stored inputs
- feedForward(INDArray, boolean) - Method in class org.deeplearning4j.nn.graph.ComputationGraph
-
Conduct forward pass using a single input array.
- feedForward(INDArray[], boolean) - Method in class org.deeplearning4j.nn.graph.ComputationGraph
-
Conduct forward pass using an array of inputs
- feedForward(INDArray[], boolean, boolean) - Method in class org.deeplearning4j.nn.graph.ComputationGraph
-
Conduct forward pass using an array of inputs.
- feedForward() - Method in class org.deeplearning4j.nn.graph.ComputationGraph
-
Conduct forward pass using the stored inputs, at test time
- feedForward(boolean) - Method in class org.deeplearning4j.nn.graph.ComputationGraph
-
Conduct forward pass using the stored inputs
- feedForward(boolean, boolean, boolean) - Method in class org.deeplearning4j.nn.graph.ComputationGraph
-
- feedForward(INDArray, boolean) - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
-
Compute activations from input to output of the output layer
- feedForward(boolean) - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
-
Compute activations from input to output of the output layer
- feedForward(boolean, boolean) - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
-
Perform feed-forward, optionally (not) clearing the layer input arrays.
Note: this method should NOT be used with clearInputs = true, unless you know what you are doing.
- feedForward() - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
-
Compute activations from input to output of the output layer
- feedForward(INDArray) - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
-
Compute activations from input to output of the output layer
- feedForward(INDArray, INDArray, INDArray) - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
-
Compute the activations from the input to the output layer, given mask arrays (that may be null)
The masking arrays are used in situations such an one-to-many and many-to-one rucerrent neural network (RNN)
designs, as well as for supporting time series of varying lengths within the same minibatch for RNNs.
- FeedForwardLayer - Class in org.deeplearning4j.nn.conf.layers
-
Created by jeffreytang on 7/21/15.
- FeedForwardLayer(FeedForwardLayer.Builder) - Constructor for class org.deeplearning4j.nn.conf.layers.FeedForwardLayer
-
- FeedForwardLayer.Builder<T extends FeedForwardLayer.Builder<T>> - Class in org.deeplearning4j.nn.conf.layers
-
- feedForwardMaskArray(INDArray, MaskState, int) - Method in interface org.deeplearning4j.nn.api.Layer
-
Feed forward the input mask array, setting in in the layer as appropriate.
- feedForwardMaskArray(INDArray, MaskState, int) - Method in interface org.deeplearning4j.nn.conf.InputPreProcessor
-
- feedForwardMaskArray(INDArray, MaskState, int) - Method in class org.deeplearning4j.nn.conf.preprocessor.BaseInputPreProcessor
-
- feedForwardMaskArray(INDArray, MaskState, int) - Method in class org.deeplearning4j.nn.conf.preprocessor.Cnn3DToFeedForwardPreProcessor
-
- feedForwardMaskArray(INDArray, MaskState, int) - Method in class org.deeplearning4j.nn.conf.preprocessor.CnnToFeedForwardPreProcessor
-
- feedForwardMaskArray(INDArray, MaskState, int) - Method in class org.deeplearning4j.nn.conf.preprocessor.CnnToRnnPreProcessor
-
- feedForwardMaskArray(INDArray, MaskState, int) - Method in class org.deeplearning4j.nn.conf.preprocessor.ComposableInputPreProcessor
-
- feedForwardMaskArray(INDArray, MaskState, int) - Method in class org.deeplearning4j.nn.conf.preprocessor.FeedForwardToCnn3DPreProcessor
-
- feedForwardMaskArray(INDArray, MaskState, int) - Method in class org.deeplearning4j.nn.conf.preprocessor.FeedForwardToCnnPreProcessor
-
- feedForwardMaskArray(INDArray, MaskState, int) - Method in class org.deeplearning4j.nn.conf.preprocessor.FeedForwardToRnnPreProcessor
-
- feedForwardMaskArray(INDArray, MaskState, int) - Method in class org.deeplearning4j.nn.conf.preprocessor.RnnToCnnPreProcessor
-
- feedForwardMaskArray(INDArray, MaskState, int) - Method in class org.deeplearning4j.nn.conf.preprocessor.RnnToFeedForwardPreProcessor
-
- feedForwardMaskArray(INDArray, MaskState, int) - Method in class org.deeplearning4j.nn.layers.AbstractLayer
-
- feedForwardMaskArray(INDArray, MaskState, int) - Method in class org.deeplearning4j.nn.layers.convolution.CnnLossLayer
-
- feedForwardMaskArray(INDArray, MaskState, int) - Method in class org.deeplearning4j.nn.layers.pooling.GlobalPoolingLayer
-
- feedForwardMaskArray(INDArray, MaskState, int) - Method in class org.deeplearning4j.nn.layers.recurrent.BidirectionalLayer
-
- feedForwardMaskArray(INDArray, MaskState, int) - Method in class org.deeplearning4j.nn.layers.recurrent.GravesBidirectionalLSTM
-
- feedForwardMaskArray(INDArray, MaskState, int) - Method in class org.deeplearning4j.nn.layers.recurrent.GravesLSTM
-
- feedForwardMaskArray(INDArray, MaskState, int) - Method in class org.deeplearning4j.nn.layers.recurrent.LastTimeStepLayer
-
- feedForwardMaskArray(INDArray, MaskState, int) - Method in class org.deeplearning4j.nn.layers.recurrent.LSTM
-
- feedForwardMaskArray(INDArray, MaskState, int) - Method in class org.deeplearning4j.nn.layers.recurrent.MaskZeroLayer
-
- feedForwardMaskArray(INDArray, MaskState, int) - Method in class org.deeplearning4j.nn.layers.recurrent.RnnLossLayer
-
- feedForwardMaskArray(INDArray, MaskState, int) - Method in class org.deeplearning4j.nn.layers.recurrent.RnnOutputLayer
-
- feedForwardMaskArray(INDArray, MaskState, int) - Method in class org.deeplearning4j.nn.layers.variational.VariationalAutoencoder
-
- feedForwardMaskArray(INDArray, MaskState, int) - Method in class org.deeplearning4j.nn.layers.wrapper.BaseWrapperLayer
-
- feedForwardMaskArray(INDArray, MaskState, int) - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
-
- feedForwardMaskArrays(INDArray[], MaskState, int) - Method in class org.deeplearning4j.nn.graph.vertex.BaseWrapperVertex
-
- feedForwardMaskArrays(INDArray[], MaskState, int) - Method in interface org.deeplearning4j.nn.graph.vertex.GraphVertex
-
- feedForwardMaskArrays(INDArray[], MaskState, int) - Method in class org.deeplearning4j.nn.graph.vertex.impl.ElementWiseVertex
-
- feedForwardMaskArrays(INDArray[], MaskState, int) - Method in class org.deeplearning4j.nn.graph.vertex.impl.InputVertex
-
- feedForwardMaskArrays(INDArray[], MaskState, int) - Method in class org.deeplearning4j.nn.graph.vertex.impl.L2NormalizeVertex
-
- feedForwardMaskArrays(INDArray[], MaskState, int) - Method in class org.deeplearning4j.nn.graph.vertex.impl.L2Vertex
-
- feedForwardMaskArrays(INDArray[], MaskState, int) - Method in class org.deeplearning4j.nn.graph.vertex.impl.LayerVertex
-
- feedForwardMaskArrays(INDArray[], MaskState, int) - Method in class org.deeplearning4j.nn.graph.vertex.impl.MergeVertex
-
- feedForwardMaskArrays(INDArray[], MaskState, int) - Method in class org.deeplearning4j.nn.graph.vertex.impl.PoolHelperVertex
-
- feedForwardMaskArrays(INDArray[], MaskState, int) - Method in class org.deeplearning4j.nn.graph.vertex.impl.PreprocessorVertex
-
- feedForwardMaskArrays(INDArray[], MaskState, int) - Method in class org.deeplearning4j.nn.graph.vertex.impl.ReshapeVertex
-
- feedForwardMaskArrays(INDArray[], MaskState, int) - Method in class org.deeplearning4j.nn.graph.vertex.impl.rnn.DuplicateToTimeSeriesVertex
-
- feedForwardMaskArrays(INDArray[], MaskState, int) - Method in class org.deeplearning4j.nn.graph.vertex.impl.rnn.LastTimeStepVertex
-
- feedForwardMaskArrays(INDArray[], MaskState, int) - Method in class org.deeplearning4j.nn.graph.vertex.impl.rnn.ReverseTimeSeriesVertex
-
- feedForwardMaskArrays(INDArray[], MaskState, int) - Method in class org.deeplearning4j.nn.graph.vertex.impl.ScaleVertex
-
- feedForwardMaskArrays(INDArray[], MaskState, int) - Method in class org.deeplearning4j.nn.graph.vertex.impl.ShiftVertex
-
- feedForwardMaskArrays(INDArray[], MaskState, int) - Method in class org.deeplearning4j.nn.graph.vertex.impl.StackVertex
-
- feedForwardMaskArrays(INDArray[], MaskState, int) - Method in class org.deeplearning4j.nn.graph.vertex.impl.SubsetVertex
-
- feedForwardMaskArrays(INDArray[], MaskState, int) - Method in class org.deeplearning4j.nn.graph.vertex.impl.UnstackVertex
-
- FeedForwardToCnn3DPreProcessor - Class in org.deeplearning4j.nn.conf.preprocessor
-
A preprocessor to allow 3D CNN and standard feed-forward network layers to be used together.
For example, DenseLayer -> Convolution3D
This does two things:
(a) Reshapes activations out of FeedFoward layer (which is 2D with shape
[numExamples, inputDepth*inputHeight*inputWidth*numChannels]) into 5d activations (with shape
[numExamples, numChannels, inputDepth, inputHeight, inputWidth]) suitable to feed into CNN layers.
(b) Reshapes 5d epsilons from 3D CNN layer, with shape
[numExamples, numChannels, inputDepth, inputHeight, inputWidth]) into 2d epsilons (with shape
[numExamples, inputDepth*inputHeight*inputWidth*numChannels]) for use in feed forward layer
- FeedForwardToCnn3DPreProcessor(int, int, int, int, boolean) - Constructor for class org.deeplearning4j.nn.conf.preprocessor.FeedForwardToCnn3DPreProcessor
-
- FeedForwardToCnn3DPreProcessor(int, int, int) - Constructor for class org.deeplearning4j.nn.conf.preprocessor.FeedForwardToCnn3DPreProcessor
-
- FeedForwardToCnnPreProcessor - Class in org.deeplearning4j.nn.conf.preprocessor
-
A preprocessor to allow CNN and standard feed-forward network layers to be used together.
For example, DenseLayer -> CNN
This does two things:
(a) Reshapes activations out of FeedFoward layer (which is 2D or 3D with shape
[numExamples, inputHeight*inputWidth*numChannels]) into 4d activations (with shape
[numExamples, numChannels, inputHeight, inputWidth]) suitable to feed into CNN layers.
(b) Reshapes 4d epsilons (weights*deltas) from CNN layer, with shape
[numExamples, numChannels, inputHeight, inputWidth]) into 2d epsilons (with shape
[numExamples, inputHeight*inputWidth*numChannels]) for use in feed forward layer
Note: numChannels is equivalent to channels or featureMaps referenced in different literature
- FeedForwardToCnnPreProcessor(int, int, int) - Constructor for class org.deeplearning4j.nn.conf.preprocessor.FeedForwardToCnnPreProcessor
-
Reshape to a channels x rows x columns tensor
- FeedForwardToCnnPreProcessor(int, int) - Constructor for class org.deeplearning4j.nn.conf.preprocessor.FeedForwardToCnnPreProcessor
-
- feedForwardToLayer(int, INDArray) - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
-
Compute the activations from the input to the specified layer.
To compute activations for all layers, use feedForward(...) methods
Note: output list includes the original input.
- feedForwardToLayer(int, INDArray, boolean) - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
-
Compute the activations from the input to the specified layer.
To compute activations for all layers, use feedForward(...) methods
Note: output list includes the original input.
- feedForwardToLayer(int, boolean) - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
-
Compute the activations from the input to the specified layer, using the currently set input for the network.
To compute activations for all layers, use feedForward(...) methods
Note: output list includes the original input.
- FeedForwardToRnnPreProcessor - Class in org.deeplearning4j.nn.conf.preprocessor
-
A preprocessor to allow RNN and feed-forward network layers to be used together.
For example, DenseLayer -> GravesLSTM
This does two things:
(a) Reshapes activations out of FeedFoward layer (which is 2D with shape
[miniBatchSize*timeSeriesLength,layerSize]) into 3d activations (with shape
[miniBatchSize,layerSize,timeSeriesLength]) suitable to feed into RNN layers.
(b) Reshapes 3d epsilons (weights*deltas from RNN layer, with shape
[miniBatchSize,layerSize,timeSeriesLength]) into 2d epsilons (with shape
[miniBatchSize*timeSeriesLength,layerSize]) for use in feed forward layer
- FeedForwardToRnnPreProcessor() - Constructor for class org.deeplearning4j.nn.conf.preprocessor.FeedForwardToRnnPreProcessor
-
- feedForwardWithKey(JavaPairRDD<K, INDArray[]>, int) - Method in class org.deeplearning4j.spark.impl.graph.SparkComputationGraph
-
Feed-forward the specified data, with the given keys.
- feedForwardWithKey(JavaPairRDD<K, INDArray>, int) - Method in class org.deeplearning4j.spark.impl.multilayer.SparkDl4jMultiLayer
-
Feed-forward the specified data, with the given keys.
- FeedForwardWithKeyFunction<K> - Class in org.deeplearning4j.spark.impl.multilayer.scoring
-
Function to feed-forward examples, and get the network output (for example, class probabilities).
- FeedForwardWithKeyFunction(Broadcast<INDArray>, Broadcast<String>, int) - Constructor for class org.deeplearning4j.spark.impl.multilayer.scoring.FeedForwardWithKeyFunction
-
- feedForwardWithKeySingle(JavaPairRDD<K, INDArray>, int) - Method in class org.deeplearning4j.spark.impl.graph.SparkComputationGraph
-
Feed-forward the specified data, with the given keys.
- feedForwardWithMaskAndKey(JavaPairRDD<K, Tuple2<INDArray, INDArray>>, int) - Method in class org.deeplearning4j.spark.impl.multilayer.SparkDl4jMultiLayer
-
Feed-forward the specified data (and optionally mask array), with the given keys.
- feedMultiDataSet(MultiDataSet, long) - Method in class org.deeplearning4j.parallelism.parameterserver.ParameterServerTrainer
-
- feedMultiDataSet(MultiDataSet, long) - Method in class org.deeplearning4j.parallelism.trainer.DefaultTrainer
-
- feedMultiDataSet(MultiDataSet, long) - Method in interface org.deeplearning4j.parallelism.trainer.Trainer
-
Train on a MultiDataSet
- fetch(int) - Method in class org.deeplearning4j.datasets.fetchers.IrisDataFetcher
-
- fetch(int) - Method in class org.deeplearning4j.datasets.fetchers.MnistDataFetcher
-
- fetch(int) - Method in interface org.deeplearning4j.datasets.iterator.DataSetFetcher
-
Deprecated.
Fetches the next dataset.
- fetch(int) - Method in class org.deeplearning4j.datasets.iterator.impl.MovingWindowDataSetFetcher
-
Fetches the next dataset.
- fetch(int) - Method in class org.deeplearning4j.models.word2vec.iterator.Word2VecDataFetcher
-
- fetcher - Variable in class org.deeplearning4j.datasets.fetchers.EmnistDataFetcher
-
- fetcher - Variable in class org.deeplearning4j.datasets.iterator.BaseDatasetIterator
-
- fetchFutures() - Method in class org.deeplearning4j.clustering.vptree.VPTree.Node
-
- fetchLabels(boolean) - Method in class org.deeplearning4j.models.word2vec.wordstore.VocabConstructor.Builder
-
Sets, if labels should be fetched, during vocab building
- fetchLabels - Variable in class org.deeplearning4j.spark.models.sequencevectors.functions.CountFunction
-
- fetchLabels - Variable in class org.deeplearning4j.spark.models.sequencevectors.functions.ExtraCountFunction
-
- ffToLayerActivationsDetached(boolean, FwdPassType, boolean, int, int[], INDArray[], INDArray[], INDArray[], boolean) - Method in class org.deeplearning4j.nn.graph.ComputationGraph
-
Feed-forward through the network - returning all array activations detached from any workspace.
- ffToLayerActivationsDetached(boolean, FwdPassType, boolean, int, INDArray, INDArray, INDArray, boolean) - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
-
Feed-forward through the network - returning all array activations in a list, detached from any workspace.
- ffToLayerActivationsInWS(boolean, int, int[], FwdPassType, boolean, INDArray[], INDArray[], INDArray[], boolean) - Method in class org.deeplearning4j.nn.graph.ComputationGraph
-
Feed-forward through the network - if workspaces are used, all returned activations will be present in workspace
WS_ALL_LAYERS_ACT.
Note: if using workspaces for training, requires that WS_ALL_LAYERS_ACT is open externally.
- ffToLayerActivationsInWs(int, FwdPassType, boolean, INDArray, INDArray, INDArray) - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
-
Feed-forward through the network at training time - returning a list of all activations in a workspace (WS_ALL_LAYERS_ACT)
if workspaces are enabled for training; or detached if no workspaces are used.
Note: if using workspaces for training, this method requires that WS_ALL_LAYERS_ACT is open externally.
If using NO workspaces, requires that no external workspace is open
Note that this method does NOT clear the inputs to each layer - instead, they are in the WS_ALL_LAYERS_ACT workspace
for use in later backprop.
- fieldsPresent() - Method in class org.deeplearning4j.ui.stats.sbe.StaticInfoDecoder
-
- fieldsPresent() - Method in class org.deeplearning4j.ui.stats.sbe.StaticInfoEncoder
-
- fieldsPresent() - Method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder
-
- fieldsPresent() - Method in class org.deeplearning4j.ui.stats.sbe.UpdateEncoder
-
- fieldsPresentId() - Static method in class org.deeplearning4j.ui.stats.sbe.StaticInfoDecoder
-
- fieldsPresentId() - Static method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder
-
- fieldsPresentMetaAttribute(MetaAttribute) - Static method in class org.deeplearning4j.ui.stats.sbe.StaticInfoDecoder
-
- fieldsPresentMetaAttribute(MetaAttribute) - Static method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder
-
- file - Variable in class org.deeplearning4j.text.sentenceiterator.FileSentenceIterator
-
- file(File) - Method in class org.deeplearning4j.ui.storage.mapdb.MapDBStatsStorage.Builder
-
- File2Stream - Class in org.ansj.dic.impl
-
将文件转换为流 file://c:/dic.txt
- File2Stream() - Constructor for class org.ansj.dic.impl.File2Stream
-
- FILE_DIR - Variable in class org.deeplearning4j.base.MnistFetcher
-
- FileCallback - Interface in org.deeplearning4j.datasets.iterator.callbacks
-
- FileDataSetIterator - Class in org.deeplearning4j.datasets.iterator.file
-
Iterate over a directory (and optionally subdirectories) containing a number of
DataSet objects that have
previously been saved to files with
DataSet.save(File).
This iterator supports the following (optional) features, depending on the constructor used:
- Recursive listing of all files (i.e., include files in subdirectories)
- Filtering based on a set of file extensions (if null, no filtering - assume all files are saved DataSet objects)
- Randomization of iteration order (default enabled, if a
Random instance is provided
- Combining and splitting of DataSets (disabled by default, or if batchSize == -1.
- FileDataSetIterator(File) - Constructor for class org.deeplearning4j.datasets.iterator.file.FileDataSetIterator
-
Create a FileDataSetIterator with the following default settings:
- Recursive: files in subdirectories are included
- Randomization: order of examples is randomized with a random RNG seed
- Batch size: default (as in the stored DataSets - no splitting/combining)
- File extensions: no filtering - all files in directory are assumed to be a DataSet
- FileDataSetIterator(File...) - Constructor for class org.deeplearning4j.datasets.iterator.file.FileDataSetIterator
-
Create a FileDataSetIterator with the following default settings:
- Recursive: files in subdirectories are included
- Randomization: order of examples is randomized with a random RNG seed
- Batch size: default (as in the stored DataSets - no splitting/combining)
- File extensions: no filtering - all files in directory are assumed to be a DataSet
- FileDataSetIterator(File, int) - Constructor for class org.deeplearning4j.datasets.iterator.file.FileDataSetIterator
-
Create a FileDataSetIterator with the specified batch size, and the following default settings:
- Recursive: files in subdirectories are included
- Randomization: order of examples is randomized with a random RNG seed
- File extensions: no filtering - all files in directory are assumed to be a DataSet
- FileDataSetIterator(File, String...) - Constructor for class org.deeplearning4j.datasets.iterator.file.FileDataSetIterator
-
Create a FileDataSetIterator with filtering based on file extensions, and the following default settings:
- Recursive: files in subdirectories are included
- Randomization: order of examples is randomized with a random RNG seed
- Batch size: default (as in the stored DataSets - no splitting/combining)
- FileDataSetIterator(File, int, String...) - Constructor for class org.deeplearning4j.datasets.iterator.file.FileDataSetIterator
-
Create a FileDataSetIterator with the specified batch size, filtering based on file extensions, and the
following default settings:
- Recursive: files in subdirectories are included
- Randomization: order of examples is randomized with a random RNG seed
- FileDataSetIterator(File, boolean, Random, int, String...) - Constructor for class org.deeplearning4j.datasets.iterator.file.FileDataSetIterator
-
Create a FileDataSetIterator with all settings specified
- FileDataSetIterator(File[], boolean, Random, int, String...) - Constructor for class org.deeplearning4j.datasets.iterator.file.FileDataSetIterator
-
Create a FileDataSetIterator with all settings specified
- FileDocumentIterator - Class in org.deeplearning4j.text.documentiterator
-
Iterate over files
- FileDocumentIterator(String) - Constructor for class org.deeplearning4j.text.documentiterator.FileDocumentIterator
-
- FileDocumentIterator(File) - Constructor for class org.deeplearning4j.text.documentiterator.FileDocumentIterator
-
- fileIterator - Variable in class org.deeplearning4j.text.sentenceiterator.FileSentenceIterator
-
- FileLabelAwareIterator - Class in org.deeplearning4j.text.documentiterator
-
This is simple filesystem-based LabelAware iterator.
- FileLabelAwareIterator() - Constructor for class org.deeplearning4j.text.documentiterator.FileLabelAwareIterator
-
- FileLabelAwareIterator(List<File>, LabelsSource) - Constructor for class org.deeplearning4j.text.documentiterator.FileLabelAwareIterator
-
- FileLabelAwareIterator.Builder - Class in org.deeplearning4j.text.documentiterator
-
- FileLabeledSentenceProvider - Class in org.deeplearning4j.iterator.provider
-
Iterate over a set of sentences/documents, where the sentences are to be loaded (as required) from the provided files.
- FileLabeledSentenceProvider(Map<String, List<File>>) - Constructor for class org.deeplearning4j.iterator.provider.FileLabeledSentenceProvider
-
- FileLabeledSentenceProvider(Map<String, List<File>>, Random) - Constructor for class org.deeplearning4j.iterator.provider.FileLabeledSentenceProvider
-
- FileMultiDataSetIterator - Class in org.deeplearning4j.datasets.iterator.file
-
Iterate over a directory (and optionally subdirectories) containing a number of
MultiDataSet objects that have
previously been saved to files with
MultiDataSet.save(File).
This iterator supports the following (optional) features, depending on the constructor used:
- Recursive listing of all files (i.e., include files in subdirectories)
- Filtering based on a set of file extensions (if null, no filtering - assume all files are saved MultiDataSet objects)
- Randomization of iteration order (default enabled, if a
Random instance is provided
- Combining and splitting of MultiDataSets (disabled by default, or if batchSize == -1.
- FileMultiDataSetIterator(File) - Constructor for class org.deeplearning4j.datasets.iterator.file.FileMultiDataSetIterator
-
Create a FileMultiDataSetIterator with the following default settings:
- Recursive: files in subdirectories are included
- Randomization: order of examples is randomized with a random RNG seed
- Batch size: default (as in the stored DataSets - no splitting/combining)
- File extensions: no filtering - all files in directory are assumed to be a DataSet
- FileMultiDataSetIterator(File...) - Constructor for class org.deeplearning4j.datasets.iterator.file.FileMultiDataSetIterator
-
Create a FileMultiDataSetIterator with the following default settings:
- Recursive: files in subdirectories are included
- Randomization: order of examples is randomized with a random RNG seed
- Batch size: default (as in the stored DataSets - no splitting/combining)
- File extensions: no filtering - all files in directory are assumed to be a DataSet
- FileMultiDataSetIterator(File, int) - Constructor for class org.deeplearning4j.datasets.iterator.file.FileMultiDataSetIterator
-
Create a FileMultiDataSetIterator with the specified batch size, and the following default settings:
- Recursive: files in subdirectories are included
- Randomization: order of examples is randomized with a random RNG seed
- File extensions: no filtering - all files in directory are assumed to be a DataSet
- FileMultiDataSetIterator(File, String...) - Constructor for class org.deeplearning4j.datasets.iterator.file.FileMultiDataSetIterator
-
Create a FileMultiDataSetIterator with filtering based on file extensions, and the following default settings:
- Recursive: files in subdirectories are included
- Randomization: order of examples is randomized with a random RNG seed
- Batch size: default (as in the stored DataSets - no splitting/combining)
- FileMultiDataSetIterator(File, int, String...) - Constructor for class org.deeplearning4j.datasets.iterator.file.FileMultiDataSetIterator
-
Create a FileMultiDataSetIterator with the specified batch size, filtering based on file extensions, and the
following default settings:
- Recursive: files in subdirectories are included
- Randomization: order of examples is randomized with a random RNG seed
- FileMultiDataSetIterator(File, boolean, Random, int, String...) - Constructor for class org.deeplearning4j.datasets.iterator.file.FileMultiDataSetIterator
-
Create a FileMultiDataSetIterator with all settings specified
- FileMultiDataSetIterator(File[], boolean, Random, int, String...) - Constructor for class org.deeplearning4j.datasets.iterator.file.FileMultiDataSetIterator
-
Create a FileMultiDataSetIterator with all settings specified
- FILENAME_AGGREGATE_TIME - Static variable in class org.deeplearning4j.spark.impl.paramavg.stats.ParameterAveragingTrainingMasterStats
-
- FILENAME_BROADCAST_CREATE - Static variable in class org.deeplearning4j.spark.impl.paramavg.stats.ParameterAveragingTrainingMasterStats
-
- FILENAME_BROADCAST_GET_STATS - Static variable in class org.deeplearning4j.spark.impl.paramavg.stats.ParameterAveragingTrainingWorkerStats
-
- FILENAME_COUNT_RDD_SIZE - Static variable in class org.deeplearning4j.spark.impl.paramavg.stats.ParameterAveragingTrainingMasterStats
-
- FILENAME_DATASET_GET_TIME_STATS - Static variable in class org.deeplearning4j.spark.api.stats.CommonSparkTrainingStats
-
- FILENAME_EXPORT_RDD_TIME - Static variable in class org.deeplearning4j.spark.impl.paramavg.stats.ParameterAveragingTrainingMasterStats
-
- FILENAME_FIT_STATS - Static variable in class org.deeplearning4j.spark.impl.paramavg.stats.ParameterAveragingTrainingWorkerStats
-
- FILENAME_FIT_TIME - Static variable in class org.deeplearning4j.spark.impl.paramavg.stats.ParameterAveragingTrainingMasterStats
-
- FILENAME_GET_INITIAL_MODEL_STATS - Static variable in class org.deeplearning4j.spark.api.stats.CommonSparkTrainingStats
-
- FILENAME_INIT_STATS - Static variable in class org.deeplearning4j.spark.impl.paramavg.stats.ParameterAveragingTrainingWorkerStats
-
- FILENAME_MAP_PARTITIONS_TIME - Static variable in class org.deeplearning4j.spark.impl.paramavg.stats.ParameterAveragingTrainingMasterStats
-
- FILENAME_PROCESS_MINIBATCH_TIME_STATS - Static variable in class org.deeplearning4j.spark.api.stats.CommonSparkTrainingStats
-
- FILENAME_PROCESS_PARAMS_TIME - Static variable in class org.deeplearning4j.spark.impl.paramavg.stats.ParameterAveragingTrainingMasterStats
-
- FILENAME_REPARTITION_STATS - Static variable in class org.deeplearning4j.spark.impl.paramavg.stats.ParameterAveragingTrainingMasterStats
-
- FILENAME_SPLIT_TIME - Static variable in class org.deeplearning4j.spark.impl.paramavg.stats.ParameterAveragingTrainingMasterStats
-
- FILENAME_TOTAL_TIME_STATS - Static variable in class org.deeplearning4j.spark.api.stats.CommonSparkTrainingStats
-
- FilenamesLabelAwareIterator - Class in org.deeplearning4j.text.documentiterator
-
This LabelAwareIterator scans folder for files, and returns them as LabelledDocuments.
- FilenamesLabelAwareIterator() - Constructor for class org.deeplearning4j.text.documentiterator.FilenamesLabelAwareIterator
-
- FilenamesLabelAwareIterator(List<File>, LabelsSource) - Constructor for class org.deeplearning4j.text.documentiterator.FilenamesLabelAwareIterator
-
- FilenamesLabelAwareIterator.Builder - Class in org.deeplearning4j.text.documentiterator
-
- FileResourceResolver - Class in com.atilika.kuromoji.util
-
- FileResourceResolver() - Constructor for class com.atilika.kuromoji.util.FileResourceResolver
-
- files - Variable in class org.deeplearning4j.text.documentiterator.FileLabelAwareIterator
-
- files - Variable in class org.deeplearning4j.text.documentiterator.FilenamesLabelAwareIterator
-
- FileSentenceIterator - Class in org.deeplearning4j.text.sentenceiterator
-
- FileSentenceIterator(SentencePreProcessor, File) - Constructor for class org.deeplearning4j.text.sentenceiterator.FileSentenceIterator
-
Takes a single file or directory
- FileSentenceIterator(File) - Constructor for class org.deeplearning4j.text.sentenceiterator.FileSentenceIterator
-
- FileSplitDataSetIterator - Class in org.deeplearning4j.datasets.iterator
-
Simple iterator working with list of files.
- FileSplitDataSetIterator(List<File>, FileCallback) - Constructor for class org.deeplearning4j.datasets.iterator.FileSplitDataSetIterator
-
- FileSplitParallelDataSetIterator - Class in org.deeplearning4j.datasets.iterator.parallel
-
- FileSplitParallelDataSetIterator(File, String, FileCallback) - Constructor for class org.deeplearning4j.datasets.iterator.parallel.FileSplitParallelDataSetIterator
-
- FileSplitParallelDataSetIterator(File, String, FileCallback, int) - Constructor for class org.deeplearning4j.datasets.iterator.parallel.FileSplitParallelDataSetIterator
-
- FileSplitParallelDataSetIterator(File, String, FileCallback, int, InequalityHandling) - Constructor for class org.deeplearning4j.datasets.iterator.parallel.FileSplitParallelDataSetIterator
-
- FileSplitParallelDataSetIterator(File, String, FileCallback, int, int, InequalityHandling) - Constructor for class org.deeplearning4j.datasets.iterator.parallel.FileSplitParallelDataSetIterator
-
- FileStatsStorage - Class in org.deeplearning4j.ui.storage
-
A StatsStorage implementation that stores UI data in a file for persistence.
Can be used for multiple instances, and across multiple independent runs.
- FileStatsStorage(File) - Constructor for class org.deeplearning4j.ui.storage.FileStatsStorage
-
- fillQueue() - Method in class org.deeplearning4j.datasets.iterator.AbstractDataSetIterator
-
- filter(Term) - Method in class org.ansj.recognition.impl.StopRecognition
-
判断一个词语是否停用..
- FilteredSequenceIterator<T extends SequenceElement> - Class in org.deeplearning4j.models.sequencevectors.iterators
-
This implementation of SequenceIterator passes each sequence through specified vocabulary, filtering out SequenceElements that are not available in Vocabulary.
- FilteredSequenceIterator(SequenceIterator<T>, VocabCache<T>) - Constructor for class org.deeplearning4j.models.sequencevectors.iterators.FilteredSequenceIterator
-
Creates Filtered SequenceIterator on top of another SequenceIterator and appropriate VocabCache instance
- filterMinWordAddVocab(Counter<String>) - Method in class org.deeplearning4j.spark.text.functions.TextPipeline
-
- filterVocab(AbstractCache<T>, int) - Method in class org.deeplearning4j.models.word2vec.wordstore.VocabConstructor
-
- finalize() - Method in class org.deeplearning4j.text.sentenceiterator.BasicLineIterator
-
- finalize() - Method in class org.deeplearning4j.text.sentenceiterator.PrefetchingSentenceIterator
-
Deprecated.
- finalizeRound(Model, Model...) - Method in class org.deeplearning4j.parallelism.factory.DefaultTrainerContext
-
- finalizeRound(Model, Model...) - Method in class org.deeplearning4j.parallelism.factory.SymmetricTrainerContext
-
- finalizeRound(Model, Model...) - Method in interface org.deeplearning4j.parallelism.factory.TrainerContext
-
This method is called at averagingFrequency
- finalizeRound(Model, Model...) - Method in class org.deeplearning4j.parallelism.parameterserver.ParameterServerTrainerContext
-
- finalizeTraining(Model, Model...) - Method in class org.deeplearning4j.parallelism.factory.DefaultTrainerContext
-
- finalizeTraining(Model, Model...) - Method in class org.deeplearning4j.parallelism.factory.SymmetricTrainerContext
-
- finalizeTraining(Model, Model...) - Method in interface org.deeplearning4j.parallelism.factory.TrainerContext
-
This method is called
- finalizeTraining(Model, Model...) - Method in class org.deeplearning4j.parallelism.parameterserver.ParameterServerTrainerContext
-
- finalizeTraining() - Method in class org.deeplearning4j.spark.parameterserver.training.SharedTrainingMaster
-
- finalMomentum - Variable in class org.deeplearning4j.plot.BarnesHutTsne
-
- finalMomentum - Variable in class org.deeplearning4j.plot.Tsne.Builder
-
- finalMomentum - Variable in class org.deeplearning4j.plot.Tsne
-
- finalProcessor - Variable in class org.deeplearning4j.streaming.routes.DL4jServeRouteBuilder
-
- finalScore(double, int, int) - Method in class org.deeplearning4j.earlystopping.scorecalc.AutoencoderScoreCalculator
-
- finalScore(U) - Method in class org.deeplearning4j.earlystopping.scorecalc.base.BaseIEvaluationScoreCalculator
-
- finalScore(double, int, int) - Method in class org.deeplearning4j.earlystopping.scorecalc.base.BaseScoreCalculator
-
- finalScore(Evaluation) - Method in class org.deeplearning4j.earlystopping.scorecalc.ClassificationScoreCalculator
-
- finalScore(double, int, int) - Method in class org.deeplearning4j.earlystopping.scorecalc.DataSetLossCalculator
-
- finalScore(RegressionEvaluation) - Method in class org.deeplearning4j.earlystopping.scorecalc.RegressionScoreCalculator
-
- finalScore(IEvaluation) - Method in class org.deeplearning4j.earlystopping.scorecalc.ROCScoreCalculator
-
- finalScore(double, int, int) - Method in class org.deeplearning4j.earlystopping.scorecalc.VAEReconErrorScoreCalculator
-
- finalScore(double, int, int) - Method in class org.deeplearning4j.earlystopping.scorecalc.VAEReconProbScoreCalculator
-
- findCreds() - Method in class org.deeplearning4j.aws.s3.BaseS3
-
- findHead(Tree) - Method in class org.deeplearning4j.text.corpora.treeparser.HeadWordFinder
-
Finds the bottom most head
- findHead2(Tree) - Method in class org.deeplearning4j.text.corpora.treeparser.HeadWordFinder
-
- findIndex(INDArray) - Method in class org.deeplearning4j.clustering.quadtree.QuadTree
-
Returns the cell of this element
- findUserDictionaryMatches(String) - Method in class com.atilika.kuromoji.dict.UserDictionary
-
Lookup words in text
- finetune() - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
-
Run SGD based on the given labels
- FineTuneConfiguration - Class in org.deeplearning4j.nn.transferlearning
-
Configuration for fine tuning.
- FineTuneConfiguration() - Constructor for class org.deeplearning4j.nn.transferlearning.FineTuneConfiguration
-
- fineTuneConfiguration(FineTuneConfiguration) - Method in class org.deeplearning4j.nn.transferlearning.TransferLearning.Builder
-
Fine tune configurations specified will overwrite the existing configuration if any
Usage example: specify a learning rate will set specified learning rate on all layers
Refer to the fineTuneConfiguration class for more details
- fineTuneConfiguration(FineTuneConfiguration) - Method in class org.deeplearning4j.nn.transferlearning.TransferLearning.GraphBuilder
-
Set parameters to selectively override existing learning parameters
Usage eg.
- FineTuneConfiguration.Builder - Class in org.deeplearning4j.nn.transferlearning
-
- finish() - Method in interface org.deeplearning4j.models.embeddings.learning.ElementsLearningAlgorithm
-
- finish() - Method in class org.deeplearning4j.models.embeddings.learning.impl.elements.CBOW
-
- finish() - Method in class org.deeplearning4j.models.embeddings.learning.impl.elements.GloVe
-
- finish() - Method in class org.deeplearning4j.models.embeddings.learning.impl.elements.SkipGram
-
- finish() - Method in class org.deeplearning4j.models.embeddings.learning.impl.sequence.DBOW
-
- finish() - Method in class org.deeplearning4j.models.embeddings.learning.impl.sequence.DM
-
- finish() - Method in interface org.deeplearning4j.models.embeddings.learning.SequenceLearningAlgorithm
-
- finish() - Method in class org.deeplearning4j.models.glove.count.ASCIICoOccurrenceReader
-
- finish() - Method in class org.deeplearning4j.models.glove.count.ASCIICoOccurrenceWriter
-
- finish() - Method in class org.deeplearning4j.models.glove.count.BinaryCoOccurrenceReader
-
- finish() - Method in class org.deeplearning4j.models.glove.count.BinaryCoOccurrenceWriter
-
- finish() - Method in interface org.deeplearning4j.models.glove.count.CoOccurenceReader
-
- finish() - Method in interface org.deeplearning4j.models.glove.count.CoOccurrenceWriter
-
Implementations of this method should close everything they use, before eradication
- finish() - Method in class org.deeplearning4j.spark.models.sequencevectors.learning.elements.BaseSparkLearningAlgorithm
-
- finish() - Method in class org.deeplearning4j.spark.models.sequencevectors.learning.sequence.BaseSparkSequenceLearningAlgorithm
-
- finish() - Method in interface org.deeplearning4j.text.invertedindex.InvertedIndex
-
Finishes saving data
- finish() - Method in class org.deeplearning4j.text.sentenceiterator.AggregatingSentenceIterator
-
- finish() - Method in class org.deeplearning4j.text.sentenceiterator.BaseSentenceIterator
-
- finish() - Method in class org.deeplearning4j.text.sentenceiterator.BasicLineIterator
-
- finish() - Method in class org.deeplearning4j.text.sentenceiterator.BasicResultSetIterator
-
- finish() - Method in class org.deeplearning4j.text.sentenceiterator.MutipleEpochsSentenceIterator
-
- finish() - Method in class org.deeplearning4j.text.sentenceiterator.PrefetchingSentenceIterator
-
Deprecated.
- finish() - Method in interface org.deeplearning4j.text.sentenceiterator.SentenceIterator
-
Allows for any finishing (closing of input streams or the like)
- finish() - Method in class org.deeplearning4j.text.sentenceiterator.StreamLineIterator
-
- finish() - Method in class org.deeplearning4j.text.sentenceiterator.SynchronizedSentenceIterator
-
- finish() - Method in class org.deeplearning4j.text.sentenceiterator.UimaResultSetIterator
-
- finishTraining(long, long) - Method in class org.deeplearning4j.spark.parameterserver.networking.SilentTrainingDriver
-
This method is used on Master only, applies buffered updates to params
- firstChild() - Method in class org.deeplearning4j.nn.layers.feedforward.autoencoder.recursive.Tree
-
- FirstIterationFunction - Class in org.deeplearning4j.spark.models.embeddings.word2vec
-
- FirstIterationFunction(Broadcast<Map<String, Object>>, Broadcast<double[]>, Broadcast<VocabCache<VocabWord>>) - Constructor for class org.deeplearning4j.spark.models.embeddings.word2vec.FirstIterationFunction
-
- FirstIterationFunctionAdapter - Class in org.deeplearning4j.spark.models.embeddings.word2vec
-
- FirstIterationFunctionAdapter(Broadcast<Map<String, Object>>, Broadcast<double[]>, Broadcast<VocabCache<VocabWord>>) - Constructor for class org.deeplearning4j.spark.models.embeddings.word2vec.FirstIterationFunctionAdapter
-
- firstOne - Variable in class org.deeplearning4j.optimize.solvers.accumulation.BasicGradientsAccumulator
-
- firstTrain - Variable in class org.deeplearning4j.datasets.iterator.DataSetIteratorSplitter
-
- firstTrain - Variable in class org.deeplearning4j.datasets.iterator.MultiDataSetIteratorSplitter
-
- fit() - Method in class org.deeplearning4j.bagofwords.vectorizer.BaseTextVectorizer
-
- fit() - Method in interface org.deeplearning4j.bagofwords.vectorizer.TextVectorizer
-
Train the model
- fit(INDArray) - Method in class org.deeplearning4j.clustering.randomprojection.RPForest
-
Build the trees from the given dataset
- fit(DataSet) - Method in class org.deeplearning4j.earlystopping.trainer.BaseEarlyStoppingTrainer
-
- fit(MultiDataSet) - Method in class org.deeplearning4j.earlystopping.trainer.BaseEarlyStoppingTrainer
-
- fit() - Method in class org.deeplearning4j.earlystopping.trainer.BaseEarlyStoppingTrainer
-
- fit(DataSet) - Method in class org.deeplearning4j.earlystopping.trainer.EarlyStoppingGraphTrainer
-
- fit(MultiDataSet) - Method in class org.deeplearning4j.earlystopping.trainer.EarlyStoppingGraphTrainer
-
- fit(DataSet) - Method in class org.deeplearning4j.earlystopping.trainer.EarlyStoppingTrainer
-
- fit(MultiDataSet) - Method in class org.deeplearning4j.earlystopping.trainer.EarlyStoppingTrainer
-
- fit() - Method in interface org.deeplearning4j.earlystopping.trainer.IEarlyStoppingTrainer
-
Conduct early stopping training
- fit(IGraph<V, E>, int) - Method in class org.deeplearning4j.graph.models.deepwalk.DeepWalk
-
Fit the model, in parallel.
- fit(GraphWalkIteratorProvider<V>) - Method in class org.deeplearning4j.graph.models.deepwalk.DeepWalk
-
- fit(GraphWalkIterator<V>) - Method in class org.deeplearning4j.graph.models.deepwalk.DeepWalk
-
Fit the DeepWalk model using a single thread using a given GraphWalkIterator.
- fit() - Method in class org.deeplearning4j.models.glove.AbstractCoOccurrences
-
- fit() - Method in class org.deeplearning4j.models.paragraphvectors.ParagraphVectors
-
- fit() - Method in class org.deeplearning4j.models.sequencevectors.SequenceVectors
-
Starts training over
- fit(DataSetIterator) - Method in interface org.deeplearning4j.nn.api.Classifier
-
Train the model based on the datasetiterator
- fit(INDArray, INDArray) - Method in interface org.deeplearning4j.nn.api.Classifier
-
Fit the model
- fit(DataSet) - Method in interface org.deeplearning4j.nn.api.Classifier
-
Fit the model
- fit(INDArray, int[]) - Method in interface org.deeplearning4j.nn.api.Classifier
-
Fit the model
- fit() - Method in interface org.deeplearning4j.nn.api.Model
-
Deprecated.
- fit(INDArray, LayerWorkspaceMgr) - Method in interface org.deeplearning4j.nn.api.Model
-
Fit the model to the given data
- fit(DataSet) - Method in interface org.deeplearning4j.nn.api.NeuralNetwork
-
This method fits model with a given DataSet
- fit(MultiDataSet) - Method in interface org.deeplearning4j.nn.api.NeuralNetwork
-
This method fits model with a given MultiDataSet
- fit(DataSetIterator) - Method in interface org.deeplearning4j.nn.api.NeuralNetwork
-
This method fits model with a given DataSetIterator
- fit(MultiDataSetIterator) - Method in interface org.deeplearning4j.nn.api.NeuralNetwork
-
This method fits model with a given MultiDataSetIterator
- fit(DataSet) - Method in class org.deeplearning4j.nn.graph.ComputationGraph
-
Fit the ComputationGraph using a DataSet.
- fit(DataSetIterator, int) - Method in class org.deeplearning4j.nn.graph.ComputationGraph
-
Perform minibatch training on all minibatches in the DataSetIterator, for the specified number of epochs.
- fit(DataSetIterator) - Method in class org.deeplearning4j.nn.graph.ComputationGraph
-
Fit the ComputationGraph using a DataSetIterator.
Note that this method can only be used with ComputationGraphs with 1 input and 1 output
Method doesn't do layerwise pretraining.
For pretraining use method pretrain..
- fit(MultiDataSet) - Method in class org.deeplearning4j.nn.graph.ComputationGraph
-
Fit the ComputationGraph using a MultiDataSet
- fit(MultiDataSetIterator, int) - Method in class org.deeplearning4j.nn.graph.ComputationGraph
-
Perform minibatch training on all minibatches in the MultiDataSetIterator, for the specified number of epochs.
- fit(MultiDataSetIterator) - Method in class org.deeplearning4j.nn.graph.ComputationGraph
-
Fit the ComputationGraph using a MultiDataSetIterator
Method doesn't do layerwise pretraining.
For pretraining use method pretrain..
- fit(INDArray[], INDArray[]) - Method in class org.deeplearning4j.nn.graph.ComputationGraph
-
Fit the ComputationGraph given arrays of inputs and labels.
- fit(INDArray[], INDArray[], INDArray[], INDArray[]) - Method in class org.deeplearning4j.nn.graph.ComputationGraph
-
Fit the ComputationGraph using the specified inputs and labels (and mask arrays)
- fit() - Method in class org.deeplearning4j.nn.graph.ComputationGraph
-
- fit(INDArray, LayerWorkspaceMgr) - Method in class org.deeplearning4j.nn.graph.ComputationGraph
-
- fit(INDArray, LayerWorkspaceMgr) - Method in class org.deeplearning4j.nn.layers.AbstractLayer
-
- fit() - Method in class org.deeplearning4j.nn.layers.AbstractLayer
-
- fit() - Method in class org.deeplearning4j.nn.layers.BaseLayer
-
- fit(INDArray, LayerWorkspaceMgr) - Method in class org.deeplearning4j.nn.layers.BaseLayer
-
- fit(DataSetIterator) - Method in class org.deeplearning4j.nn.layers.BaseOutputLayer
-
- fit(INDArray, INDArray) - Method in class org.deeplearning4j.nn.layers.BaseOutputLayer
-
Fit the model
- fit(DataSet) - Method in class org.deeplearning4j.nn.layers.BaseOutputLayer
-
Fit the model
- fit(INDArray, int[]) - Method in class org.deeplearning4j.nn.layers.BaseOutputLayer
-
Fit the model
- fit(INDArray, LayerWorkspaceMgr) - Method in class org.deeplearning4j.nn.layers.BaseOutputLayer
-
Fit the model to the given data
- fit(DataSetIterator) - Method in class org.deeplearning4j.nn.layers.convolution.CnnLossLayer
-
- fit(INDArray, INDArray) - Method in class org.deeplearning4j.nn.layers.convolution.CnnLossLayer
-
- fit(DataSet) - Method in class org.deeplearning4j.nn.layers.convolution.CnnLossLayer
-
- fit(INDArray, int[]) - Method in class org.deeplearning4j.nn.layers.convolution.CnnLossLayer
-
- fit(INDArray, LayerWorkspaceMgr) - Method in class org.deeplearning4j.nn.layers.convolution.ConvolutionLayer
-
- fit() - Method in class org.deeplearning4j.nn.layers.convolution.subsampling.Subsampling3DLayer
-
- fit(INDArray, LayerWorkspaceMgr) - Method in class org.deeplearning4j.nn.layers.convolution.subsampling.Subsampling3DLayer
-
- fit() - Method in class org.deeplearning4j.nn.layers.convolution.subsampling.SubsamplingLayer
-
- fit(INDArray, LayerWorkspaceMgr) - Method in class org.deeplearning4j.nn.layers.convolution.subsampling.SubsamplingLayer
-
- fit() - Method in class org.deeplearning4j.nn.layers.convolution.upsampling.Upsampling2D
-
- fit(INDArray, LayerWorkspaceMgr) - Method in class org.deeplearning4j.nn.layers.convolution.upsampling.Upsampling2D
-
- fit() - Method in class org.deeplearning4j.nn.layers.convolution.upsampling.Upsampling3D
-
- fit(INDArray, LayerWorkspaceMgr) - Method in class org.deeplearning4j.nn.layers.convolution.upsampling.Upsampling3D
-
- fit(INDArray, LayerWorkspaceMgr) - Method in class org.deeplearning4j.nn.layers.DropoutLayer
-
- fit(INDArray, LayerWorkspaceMgr) - Method in class org.deeplearning4j.nn.layers.feedforward.dense.DenseLayer
-
- fit() - Method in class org.deeplearning4j.nn.layers.FrozenLayer
-
- fit(INDArray, LayerWorkspaceMgr) - Method in class org.deeplearning4j.nn.layers.FrozenLayer
-
- fit() - Method in class org.deeplearning4j.nn.layers.FrozenLayerWithBackprop
-
- fit(INDArray, LayerWorkspaceMgr) - Method in class org.deeplearning4j.nn.layers.FrozenLayerWithBackprop
-
- fit(INDArray, LayerWorkspaceMgr) - Method in class org.deeplearning4j.nn.layers.LossLayer
-
- fit(DataSetIterator) - Method in class org.deeplearning4j.nn.layers.LossLayer
-
- fit(INDArray, INDArray) - Method in class org.deeplearning4j.nn.layers.LossLayer
-
Fit the model
- fit(DataSet) - Method in class org.deeplearning4j.nn.layers.LossLayer
-
Fit the model
- fit(INDArray, int[]) - Method in class org.deeplearning4j.nn.layers.LossLayer
-
Fit the model
- fit(INDArray, LayerWorkspaceMgr) - Method in class org.deeplearning4j.nn.layers.normalization.BatchNormalization
-
- fit(INDArray, LayerWorkspaceMgr) - Method in class org.deeplearning4j.nn.layers.normalization.LocalResponseNormalization
-
- fit(DataSetIterator) - Method in class org.deeplearning4j.nn.layers.objdetect.Yolo2OutputLayer
-
- fit(INDArray, INDArray) - Method in class org.deeplearning4j.nn.layers.objdetect.Yolo2OutputLayer
-
- fit(DataSet) - Method in class org.deeplearning4j.nn.layers.objdetect.Yolo2OutputLayer
-
- fit(INDArray, int[]) - Method in class org.deeplearning4j.nn.layers.objdetect.Yolo2OutputLayer
-
- fit() - Method in class org.deeplearning4j.nn.layers.recurrent.BidirectionalLayer
-
- fit(INDArray, LayerWorkspaceMgr) - Method in class org.deeplearning4j.nn.layers.recurrent.BidirectionalLayer
-
- fit(DataSetIterator) - Method in class org.deeplearning4j.nn.layers.recurrent.RnnLossLayer
-
- fit(INDArray, INDArray) - Method in class org.deeplearning4j.nn.layers.recurrent.RnnLossLayer
-
- fit(DataSet) - Method in class org.deeplearning4j.nn.layers.recurrent.RnnLossLayer
-
- fit(INDArray, int[]) - Method in class org.deeplearning4j.nn.layers.recurrent.RnnLossLayer
-
- fit(INDArray, LayerWorkspaceMgr) - Method in class org.deeplearning4j.nn.layers.variational.VariationalAutoencoder
-
- fit() - Method in class org.deeplearning4j.nn.layers.variational.VariationalAutoencoder
-
- fit() - Method in class org.deeplearning4j.nn.layers.wrapper.BaseWrapperLayer
-
- fit(INDArray, LayerWorkspaceMgr) - Method in class org.deeplearning4j.nn.layers.wrapper.BaseWrapperLayer
-
- fit(DataSetIterator, int) - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
-
Perform minibatch training on all minibatches in the DataSetIterator, for the specified number of epochs.
- fit(DataSetIterator) - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
-
Perform minibatch training on all minibatches in the DataSetIterator.
Note that this method does not do layerwise pretraining.
For pretraining use method pretrain..
- fit(INDArray, INDArray) - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
-
Fit the model
- fit(INDArray, INDArray, INDArray, INDArray) - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
-
Fit the model
- fit(INDArray, LayerWorkspaceMgr) - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
-
- fit(DataSet) - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
-
Fit the model
- fit(INDArray, int[]) - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
-
Fit the model
- fit() - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
-
- fit(MultiDataSet) - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
-
- fit(MultiDataSetIterator, int) - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
-
Perform minibatch training on all minibatches in the MultiDataSetIterator, for the specified number of epochs.
- fit(MultiDataSetIterator) - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
-
Perform minibatch training on all minibatches in the MultiDataSetIterator.
Note: The MultiDataSets in the MultiDataSetIterator must have exactly 1 input and output array (as
MultiLayerNetwork only supports 1 input and 1 output)
- fit() - Method in class org.deeplearning4j.parallelism.EarlyStoppingParallelTrainer
-
- fit(MultiDataSetIterator) - Method in class org.deeplearning4j.parallelism.ParallelWrapper
-
- fit(DataSetIterator) - Method in class org.deeplearning4j.parallelism.ParallelWrapper
-
This method takes DataSetIterator, and starts training over it by scheduling DataSets to different executors
- fit(DataSet) - Method in class org.deeplearning4j.parallelism.trainer.DefaultTrainer
-
- fit(MultiDataSet) - Method in class org.deeplearning4j.parallelism.trainer.DefaultTrainer
-
- fit() - Method in class org.deeplearning4j.plot.BarnesHutTsne
-
- fit(INDArray) - Method in class org.deeplearning4j.plot.BarnesHutTsne
-
- fit(INDArray, LayerWorkspaceMgr) - Method in class org.deeplearning4j.plot.BarnesHutTsne
-
- fit(INDArray, int) - Method in class org.deeplearning4j.plot.BarnesHutTsne
-
- fit(JavaRDD<DataSet>) - Method in class org.deeplearning4j.spark.earlystopping.BaseSparkEarlyStoppingTrainer
-
- fit() - Method in class org.deeplearning4j.spark.earlystopping.BaseSparkEarlyStoppingTrainer
-
- fit(JavaRDD<DataSet>) - Method in class org.deeplearning4j.spark.earlystopping.SparkEarlyStoppingGraphTrainer
-
- fit(JavaRDD<DataSet>) - Method in class org.deeplearning4j.spark.earlystopping.SparkEarlyStoppingTrainer
-
- fit(RDD<DataSet>) - Method in class org.deeplearning4j.spark.impl.graph.SparkComputationGraph
-
Fit the ComputationGraph with the given data set
- fit(JavaRDD<DataSet>) - Method in class org.deeplearning4j.spark.impl.graph.SparkComputationGraph
-
Fit the ComputationGraph with the given data set
- fit(String) - Method in class org.deeplearning4j.spark.impl.graph.SparkComputationGraph
-
Fit the SparkComputationGraph network using a directory of serialized DataSet objects
The assumption here is that the directory contains a number of DataSet objects, each serialized using
DataSet.save(OutputStream)
- fit(String, int) - Method in class org.deeplearning4j.spark.impl.graph.SparkComputationGraph
-
- fit(RDD<DataSet>) - Method in class org.deeplearning4j.spark.impl.multilayer.SparkDl4jMultiLayer
-
Fit the DataSet RDD.
- fit(JavaRDD<DataSet>) - Method in class org.deeplearning4j.spark.impl.multilayer.SparkDl4jMultiLayer
-
Fit the DataSet RDD
- fit(String) - Method in class org.deeplearning4j.spark.impl.multilayer.SparkDl4jMultiLayer
-
Fit the SparkDl4jMultiLayer network using a directory of serialized DataSet objects
The assumption here is that the directory contains a number of DataSet objects, each serialized using
DataSet.save(OutputStream)
- fit(String, int) - Method in class org.deeplearning4j.spark.impl.multilayer.SparkDl4jMultiLayer
-
- fit() - Method in class org.deeplearning4j.spark.models.sequencevectors.SparkSequenceVectors
-
Deprecated.
- fit() - Method in class org.deeplearning4j.spark.models.word2vec.SparkWord2Vec
-
Deprecated.
- fitContinuousLabeledPoint(JavaRDD<LabeledPoint>) - Method in class org.deeplearning4j.spark.impl.multilayer.SparkDl4jMultiLayer
-
Fits a MultiLayerNetwork using Spark MLLib LabeledPoint instances
This will convert labeled points that have continuous labels used for regression to the internal
DL4J data format and train the model on that
- fitFeaturized(MultiDataSetIterator) - Method in class org.deeplearning4j.nn.transferlearning.TransferLearningHelper
-
Fit from a featurized dataset.
- fitFeaturized(MultiDataSet) - Method in class org.deeplearning4j.nn.transferlearning.TransferLearningHelper
-
- fitFeaturized(DataSet) - Method in class org.deeplearning4j.nn.transferlearning.TransferLearningHelper
-
- fitFeaturized(DataSetIterator) - Method in class org.deeplearning4j.nn.transferlearning.TransferLearningHelper
-
- fitLabeledPoint(JavaRDD<LabeledPoint>) - Method in class org.deeplearning4j.spark.impl.multilayer.SparkDl4jMultiLayer
-
Fit a MultiLayerNetwork using Spark MLLib LabeledPoint instances.
- fitLabelledDocuments(JavaRDD<LabelledDocument>) - Method in class org.deeplearning4j.spark.models.paragraphvectors.SparkParagraphVectors
-
This method builds ParagraphVectors model, expecting JavaRDD.
- fitLists(JavaRDD<List<T>>) - Method in class org.deeplearning4j.spark.models.sequencevectors.SparkSequenceVectors
-
Utility method.
- fitMulti(JavaRDD<MultiDataSet>) - Method in class org.deeplearning4j.spark.earlystopping.BaseSparkEarlyStoppingTrainer
-
- fitMulti(JavaRDD<MultiDataSet>) - Method in class org.deeplearning4j.spark.earlystopping.SparkEarlyStoppingGraphTrainer
-
- fitMulti(JavaRDD<MultiDataSet>) - Method in class org.deeplearning4j.spark.earlystopping.SparkEarlyStoppingTrainer
-
- fitMultiDataSet(RDD<MultiDataSet>) - Method in class org.deeplearning4j.spark.impl.graph.SparkComputationGraph
-
Fit the ComputationGraph with the given data set
- fitMultiDataSet(JavaRDD<MultiDataSet>) - Method in class org.deeplearning4j.spark.impl.graph.SparkComputationGraph
-
Fit the ComputationGraph with the given data set
- fitMultiDataSet(String) - Method in class org.deeplearning4j.spark.impl.graph.SparkComputationGraph
-
Fit the SparkComputationGraph network using a directory of serialized MultiDataSet objects
The assumption here is that the directory contains a number of serialized MultiDataSet objects
- fitMultiDataSet(String, int) - Method in class org.deeplearning4j.spark.impl.graph.SparkComputationGraph
-
- fitMultipleFiles(JavaPairRDD<String, String>) - Method in class org.deeplearning4j.spark.models.paragraphvectors.SparkParagraphVectors
-
This method builds ParagraphVectors model, expecting JavaPairRDD with key as label, and value as document-in-a-string.
- fitPaths(JavaRDD<String>) - Method in class org.deeplearning4j.spark.impl.graph.SparkComputationGraph
-
Fit the network using a list of paths for serialized DataSet objects.
- fitPaths(JavaRDD<String>) - Method in class org.deeplearning4j.spark.impl.multilayer.SparkDl4jMultiLayer
-
Fit the network using a list of paths for serialized DataSet objects.
- fitPathsMultiDataSet(JavaRDD<String>) - Method in class org.deeplearning4j.spark.impl.graph.SparkComputationGraph
-
Fit the network using a list of paths for serialized MultiDataSet objects.
- fitSentences(JavaRDD<String>) - Method in class org.deeplearning4j.spark.models.word2vec.SparkWord2Vec
-
- fitSequences(JavaRDD<Sequence<T>>) - Method in class org.deeplearning4j.spark.models.sequencevectors.SparkSequenceVectors
-
Base training entry point
- FixedClusterCountStrategy - Class in org.deeplearning4j.clustering.strategy
-
- FixedClusterCountStrategy(Integer, String, boolean, boolean) - Constructor for class org.deeplearning4j.clustering.strategy.FixedClusterCountStrategy
-
- FixedIterationCountCondition - Class in org.deeplearning4j.clustering.condition
-
- FixedIterationCountCondition(int) - Constructor for class org.deeplearning4j.clustering.condition.FixedIterationCountCondition
-
- flag - Variable in class org.ansj.domain.NumNatureAttr
-
- flag - Variable in class org.ansj.domain.PersonNatureAttr
-
- FlatModelUtils<T extends SequenceElement> - Class in org.deeplearning4j.models.embeddings.reader.impl
-
This model reader is suited for model tests, and for cases where flat scan against elements is required.
- FlatModelUtils() - Constructor for class org.deeplearning4j.models.embeddings.reader.impl.FlatModelUtils
-
- flattenedGradients - Variable in class org.deeplearning4j.nn.graph.ComputationGraph
-
- flattenedGradients - Variable in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
-
- flattenedParams - Variable in class org.deeplearning4j.nn.graph.ComputationGraph
-
- flattenedParams - Variable in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
-
- flatteningOrderForVariable(String) - Method in class org.deeplearning4j.nn.gradient.DefaultGradient
-
- flatteningOrderForVariable(String) - Method in interface org.deeplearning4j.nn.gradient.Gradient
-
Return the gradient flattening order for the specified variable, or null if it is not explicitly set
- FloatsDataSetIterator - Class in org.deeplearning4j.datasets.iterator
-
float[] wrapper for DataSetIterator impementation.
- FloatsDataSetIterator(Iterable<Pair<float[], float[]>>, int) - Constructor for class org.deeplearning4j.datasets.iterator.FloatsDataSetIterator
-
- floatValue(StyleDiv.FloatValue) - Method in class org.deeplearning4j.ui.components.component.style.StyleDiv.Builder
-
CSS float styling option
- FoldBetweenPartitionFunction - Class in org.deeplearning4j.spark.text.functions
-
- FoldBetweenPartitionFunction(Broadcast<Counter<Integer>>) - Constructor for class org.deeplearning4j.spark.text.functions.FoldBetweenPartitionFunction
-
- foldersToScan - Variable in class org.deeplearning4j.text.documentiterator.FileLabelAwareIterator.Builder
-
- foldersToScan - Variable in class org.deeplearning4j.text.documentiterator.FilenamesLabelAwareIterator.Builder
-
- FoldWithinPartitionFunction - Class in org.deeplearning4j.spark.text.functions
-
- FoldWithinPartitionFunction(Accumulator<Counter<Integer>>) - Constructor for class org.deeplearning4j.spark.text.functions.FoldWithinPartitionFunction
-
- font(String) - Method in class org.deeplearning4j.ui.components.text.style.StyleText.Builder
-
Specify the font to be used for the text
- fontSize(double) - Method in class org.deeplearning4j.ui.components.text.style.StyleText.Builder
-
Size of the font (pt)
- fOrder - Variable in class org.deeplearning4j.datasets.fetchers.MnistDataFetcher
-
- forEachRemaining(Consumer<? super MultiDataSet>) - Method in class org.deeplearning4j.spark.parameterserver.iterators.MultiPdsIterator
-
- forEachRemaining(Consumer<? super DataSet>) - Method in class org.deeplearning4j.spark.parameterserver.iterators.PdsIterator
-
- forEachRemaining(Consumer<? super E>) - Method in class org.deeplearning4j.spark.parameterserver.iterators.VirtualIterator
-
- ForeignPersonRecognition - Class in org.ansj.recognition.arrimpl
-
外国人名识别
- ForeignPersonRecognition() - Constructor for class org.ansj.recognition.arrimpl.ForeignPersonRecognition
-
- forests - Variable in class org.ansj.splitWord.Analysis
-
- forgetGateBiasInit - Variable in class org.deeplearning4j.nn.conf.layers.AbstractLSTM.Builder
-
- forgetGateBiasInit(double) - Method in class org.deeplearning4j.nn.conf.layers.AbstractLSTM.Builder
-
Set forget gate bias initalizations.
- forgetGateBiasInit - Variable in class org.deeplearning4j.nn.conf.layers.AbstractLSTM
-
- forgetGateBiasInit(double) - Method in class org.deeplearning4j.nn.conf.layers.GravesBidirectionalLSTM.Builder
-
Deprecated.
Set forget gate bias initalizations.
- format(PatriciaTrie<V>) - Method in class com.atilika.kuromoji.trie.PatriciaTrieFormatter
-
Format trie
- format(PatriciaTrie<V>, boolean) - Method in class com.atilika.kuromoji.trie.PatriciaTrieFormatter
-
Format trie
- format(PatriciaTrie<V>, File) - Method in class com.atilika.kuromoji.trie.PatriciaTrieFormatter
-
Format trie and write to file
- format(PatriciaTrie<V>, File, boolean) - Method in class com.atilika.kuromoji.trie.PatriciaTrieFormatter
-
Format trie and write to file
- format(ViterbiLattice) - Method in class com.atilika.kuromoji.viterbi.ViterbiFormatter
-
- format(ViterbiLattice, List<ViterbiNode>) - Method in class com.atilika.kuromoji.viterbi.ViterbiFormatter
-
- format(double, int) - Method in class org.deeplearning4j.eval.curves.BaseCurve
-
- FORWARD_PREFIX - Static variable in class org.deeplearning4j.nn.params.BidirectionalParamInitializer
-
- frame - Variable in class org.deeplearning4j.spark.models.sequencevectors.learning.elements.SparkCBOW
-
- frame - Variable in class org.deeplearning4j.spark.models.sequencevectors.learning.elements.SparkSkipGram
-
- frameId - Variable in class org.deeplearning4j.spark.parameterserver.networking.messages.SilentUpdatesMessage
-
- frameSequence(Sequence<ShallowSequenceElement>, AtomicLong, double) - Method in class org.deeplearning4j.spark.models.sequencevectors.learning.elements.SparkCBOW
-
- frameSequence(Sequence<ShallowSequenceElement>, AtomicLong, double) - Method in class org.deeplearning4j.spark.models.sequencevectors.learning.elements.SparkSkipGram
-
- frameSequence(Sequence<ShallowSequenceElement>, AtomicLong, double) - Method in class org.deeplearning4j.spark.models.sequencevectors.learning.sequence.SparkDBOW
-
- frameSequence(Sequence<ShallowSequenceElement>, AtomicLong, double) - Method in class org.deeplearning4j.spark.models.sequencevectors.learning.sequence.SparkDM
-
- frameSequence(Sequence<ShallowSequenceElement>, AtomicLong, double) - Method in interface org.deeplearning4j.spark.models.sequencevectors.learning.SparkElementsLearningAlgorithm
-
- frequency - Variable in class org.ansj.domain.TermNature
-
- frequency - Variable in class org.deeplearning4j.optimize.listeners.EvaluativeListener
-
- from - Variable in class org.ansj.app.crf.pojo.Element
-
- from() - Method in class org.ansj.domain.Term
-
- from - Variable in class org.ansj.recognition.impl.NatureRecognition.NatureTerm
-
- from - Variable in class org.deeplearning4j.nn.conf.graph.UnstackVertex
-
- fromBinary(JavaPairRDD<String, PortableDataStream>, RecordReader) - Static method in class org.deeplearning4j.spark.util.MLLibUtil
-
Convert a traditional sc.binaryFiles
in to something usable for machine learning
- fromBinary(JavaRDD<Tuple2<String, PortableDataStream>>, RecordReader) - Static method in class org.deeplearning4j.spark.util.MLLibUtil
-
Convert a traditional sc.binaryFiles
in to something usable for machine learning
- fromBytesSerializable(byte[]) - Static method in class org.deeplearning4j.ui.stats.impl.SbeUtil
-
- fromContinuousLabeledPoint(JavaSparkContext, JavaRDD<LabeledPoint>) - Static method in class org.deeplearning4j.spark.util.MLLibUtil
-
- fromContinuousLabeledPoint(JavaRDD<LabeledPoint>) - Static method in class org.deeplearning4j.spark.util.MLLibUtil
-
Converts a continuous JavaRDD LabeledPoint to a JavaRDD DataSet.
- fromContinuousLabeledPoint(JavaRDD<LabeledPoint>, boolean) - Static method in class org.deeplearning4j.spark.util.MLLibUtil
-
Converts a continuous JavaRDD LabeledPoint to a JavaRDD DataSet.
- fromDataSet(DataSet) - Static method in class org.deeplearning4j.nearestneighbor.model.BatchRecord
-
Return a batch record based on a dataset
- fromDataSet(JavaSparkContext, JavaRDD<DataSet>) - Static method in class org.deeplearning4j.spark.util.MLLibUtil
-
- fromDataSet(JavaRDD<DataSet>) - Static method in class org.deeplearning4j.spark.util.MLLibUtil
-
Convert an rdd of data set in to labeled point.
- fromDataSet(JavaRDD<DataSet>, boolean) - Static method in class org.deeplearning4j.spark.util.MLLibUtil
-
Convert an rdd of data set in to labeled point.
- fromFileString(String) - Static method in class org.deeplearning4j.optimize.listeners.checkpoint.Checkpoint
-
- fromIActivation(IActivation) - Static method in class org.deeplearning4j.nn.conf.layers.samediff.SameDiffLayerUtils
-
- fromJson(String, Class<T>) - Static method in class org.deeplearning4j.eval.BaseEvaluation
-
- fromJson(String, Class<T>) - Static method in class org.deeplearning4j.eval.curves.BaseCurve
-
- fromJson(String, Class<T>) - Static method in class org.deeplearning4j.eval.curves.BaseHistogram
-
- fromJson(String) - Static method in class org.deeplearning4j.eval.curves.Histogram
-
- fromJson(String) - Static method in class org.deeplearning4j.eval.curves.PrecisionRecallCurve
-
- fromJson(String) - Static method in class org.deeplearning4j.eval.curves.RocCurve
-
- fromJson(String) - Static method in class org.deeplearning4j.eval.Evaluation
-
- fromJson(String) - Static method in class org.deeplearning4j.eval.EvaluationBinary
-
- fromJson(String) - Static method in class org.deeplearning4j.models.embeddings.loader.VectorsConfiguration
-
- fromJson(String) - Static method in class org.deeplearning4j.models.word2vec.wordstore.VocabularyWord
-
- fromJson(String) - Static method in class org.deeplearning4j.nn.conf.ComputationGraphConfiguration
-
Create a computation graph configuration from json
- fromJson(String) - Static method in class org.deeplearning4j.nn.conf.memory.MemoryReport
-
- fromJson(String) - Static method in class org.deeplearning4j.nn.conf.MultiLayerConfiguration
-
Create a neural net configuration from json
- fromJson(String) - Static method in class org.deeplearning4j.nn.conf.NeuralNetConfiguration
-
Create a neural net configuration from json
- fromJson(String) - Static method in class org.deeplearning4j.nn.transferlearning.FineTuneConfiguration
-
- fromJson(String) - Static method in class org.deeplearning4j.spark.impl.paramavg.ParameterAveragingTrainingMaster
-
- fromJson(String) - Static method in class org.deeplearning4j.spark.parameterserver.training.SharedTrainingMaster
-
- fromLabeledPoint(JavaRDD<LabeledPoint>, int, int) - Static method in class org.deeplearning4j.spark.util.MLLibUtil
-
Convert an rdd
of labeled point
based on the specified batch size
in to data set
- fromLabeledPoint(JavaSparkContext, JavaRDD<LabeledPoint>, int) - Static method in class org.deeplearning4j.spark.util.MLLibUtil
-
- fromLabeledPoint(JavaRDD<LabeledPoint>, int) - Static method in class org.deeplearning4j.spark.util.MLLibUtil
-
Converts JavaRDD labeled points to JavaRDD datasets.
- fromLabeledPoint(JavaRDD<LabeledPoint>, int, boolean) - Static method in class org.deeplearning4j.spark.util.MLLibUtil
-
Converts JavaRDD labeled points to JavaRDD DataSets.
- fromPair(Pair<InMemoryLookupTable, VocabCache>) - Static method in class org.deeplearning4j.models.embeddings.loader.WordVectorSerializer
-
Load word vectors from the given pair
- fromRow(DataSet) - Static method in class org.deeplearning4j.nearestneighbor.model.CSVRecord
-
Instantiate a csv record from a vector
given either an input dataset and a
one hot matrix, the index will be appended to
the end of the record, or for regression
it will append all values in the labels
- fromString(String, String) - Static method in class org.deeplearning4j.clustering.util.MathUtils
-
This will take a given string and separator and convert it to an equivalent
double array.
- fromSystem() - Static method in class org.deeplearning4j.perf.listener.HardwareMetric
-
- fromSystem(SystemInfo) - Static method in class org.deeplearning4j.perf.listener.HardwareMetric
-
Returns the relevant information
needed for system diagnostics
based on the SystemInfo
- fromSystem(SystemInfo, String) - Static method in class org.deeplearning4j.perf.listener.HardwareMetric
-
Returns the relevant information
needed for system diagnostics
based on the SystemInfo
- fromTableAndVocab(WeightLookupTable, VocabCache) - Static method in class org.deeplearning4j.models.embeddings.loader.WordVectorSerializer
-
Load word vectors for the given vocab and table
- fromYaml(String, Class<T>) - Static method in class org.deeplearning4j.eval.BaseEvaluation
-
- fromYaml(String, Class<T>) - Static method in class org.deeplearning4j.eval.curves.BaseCurve
-
- fromYaml(String, Class<T>) - Static method in class org.deeplearning4j.eval.curves.BaseHistogram
-
- fromYaml(String) - Static method in class org.deeplearning4j.eval.curves.Histogram
-
- fromYaml(String) - Static method in class org.deeplearning4j.eval.curves.PrecisionRecallCurve
-
- fromYaml(String) - Static method in class org.deeplearning4j.eval.curves.RocCurve
-
- fromYaml(String) - Static method in class org.deeplearning4j.eval.Evaluation
-
- fromYaml(String) - Static method in class org.deeplearning4j.eval.EvaluationBinary
-
- fromYaml(String) - Static method in class org.deeplearning4j.nn.conf.ComputationGraphConfiguration
-
Create a neural net configuration from json
- fromYaml(String) - Static method in class org.deeplearning4j.nn.conf.memory.MemoryReport
-
- fromYaml(String) - Static method in class org.deeplearning4j.nn.conf.MultiLayerConfiguration
-
Create a neural net configuration from json
- fromYaml(String) - Static method in class org.deeplearning4j.nn.conf.NeuralNetConfiguration
-
Create a neural net configuration from json
- fromYaml(String) - Static method in class org.deeplearning4j.nn.transferlearning.FineTuneConfiguration
-
- fromYaml(String) - Static method in class org.deeplearning4j.perf.listener.HardwareMetric
-
- fromYaml(String) - Static method in class org.deeplearning4j.spark.impl.paramavg.ParameterAveragingTrainingMaster
-
- fromYaml(String) - Static method in class org.deeplearning4j.spark.parameterserver.training.SharedTrainingMaster
-
- FrozenLayer - Class in org.deeplearning4j.nn.conf.layers.misc
-
Created by Alex on 10/07/2017.
- FrozenLayer(Layer) - Constructor for class org.deeplearning4j.nn.conf.layers.misc.FrozenLayer
-
- FrozenLayer - Class in org.deeplearning4j.nn.layers
-
For purposes of transfer learning
A frozen layers wraps another dl4j layer within it.
- FrozenLayer(Layer) - Constructor for class org.deeplearning4j.nn.layers.FrozenLayer
-
- FrozenLayer.Builder - Class in org.deeplearning4j.nn.conf.layers.misc
-
- FrozenLayerParamInitializer - Class in org.deeplearning4j.nn.params
-
- FrozenLayerParamInitializer() - Constructor for class org.deeplearning4j.nn.params.FrozenLayerParamInitializer
-
- FrozenLayerWithBackprop - Class in org.deeplearning4j.nn.conf.layers.misc
-
Frozen layer freezes parameters of the layer it wraps, but allows the backpropagation to continue.
- FrozenLayerWithBackprop(Layer) - Constructor for class org.deeplearning4j.nn.conf.layers.misc.FrozenLayerWithBackprop
-
- FrozenLayerWithBackprop - Class in org.deeplearning4j.nn.layers
-
Frozen layer freezes parameters of the layer it wraps, but allows the backpropagation to continue.
- FrozenLayerWithBackprop(Layer) - Constructor for class org.deeplearning4j.nn.layers.FrozenLayerWithBackprop
-
- FrozenLayerWithBackpropParamInitializer - Class in org.deeplearning4j.nn.params
-
- FrozenLayerWithBackpropParamInitializer() - Constructor for class org.deeplearning4j.nn.params.FrozenLayerWithBackpropParamInitializer
-
- FrozenVertex - Class in org.deeplearning4j.nn.conf.graph
-
FrozenVertex is used for the purposes of transfer learning
A frozen layers wraps another DL4J GraphVertex within it.
- FrozenVertex(GraphVertex) - Constructor for class org.deeplearning4j.nn.conf.graph.FrozenVertex
-
- FrozenVertex - Class in org.deeplearning4j.nn.graph.vertex.impl
-
FrozenVertex is used for the purposes of transfer learning
A frozen layers wraps another DL4J GraphVertex within it.
- FrozenVertex(GraphVertex) - Constructor for class org.deeplearning4j.nn.graph.vertex.impl.FrozenVertex
-
- fullyConnected(int, int, double) - Static method in class org.deeplearning4j.zoo.model.helper.FaceNetHelper
-
- function(Function<T, Result>) - Static method in class org.deeplearning4j.nearestneighbor.server.FunctionUtil
-
- function(Function<T, Result>) - Static method in class org.deeplearning4j.ui.play.misc.FunctionUtil
-
- function0(Supplier<Result>) - Static method in class org.deeplearning4j.nearestneighbor.server.FunctionUtil
-
- function0(Supplier<Result>) - Static method in class org.deeplearning4j.ui.play.misc.FunctionUtil
-
- FunctionType - Enum in org.deeplearning4j.ui.api
-
Enumeration for the type of function.
- FunctionUtil - Class in org.deeplearning4j.nearestneighbor.server
-
Utility methods for Routing
- FunctionUtil() - Constructor for class org.deeplearning4j.nearestneighbor.server.FunctionUtil
-
- FunctionUtil - Class in org.deeplearning4j.ui.play.misc
-
Utility methods for Routing
- FunctionUtil() - Constructor for class org.deeplearning4j.ui.play.misc.FunctionUtil
-
- futureLeft - Variable in class org.deeplearning4j.clustering.vptree.VPTree.Node
-
- futureRight - Variable in class org.deeplearning4j.clustering.vptree.VPTree.Node
-
- fwdPassOutput - Variable in class org.deeplearning4j.nn.layers.recurrent.FwdPassReturn
-
- fwdPassOutputAsArrays - Variable in class org.deeplearning4j.nn.layers.recurrent.FwdPassReturn
-
- FwdPassReturn - Class in org.deeplearning4j.nn.layers.recurrent
-
Created by benny on 12/31/15.
- FwdPassReturn() - Constructor for class org.deeplearning4j.nn.layers.recurrent.FwdPassReturn
-
- FwdPassType - Enum in org.deeplearning4j.nn.api
-
Type of forward pass to do.
- fz - Variable in class org.deeplearning4j.nn.layers.recurrent.FwdPassReturn
-
- ga - Variable in class org.deeplearning4j.nn.layers.recurrent.FwdPassReturn
-
- gamma - Variable in class org.deeplearning4j.nn.conf.layers.BatchNormalization.Builder
-
- gamma(double) - Method in class org.deeplearning4j.nn.conf.layers.BatchNormalization.Builder
-
- gamma - Variable in class org.deeplearning4j.nn.conf.layers.BatchNormalization
-
- GAMMA - Static variable in class org.deeplearning4j.nn.params.BatchNormalizationParamInitializer
-
- gammaConstraints - Variable in class org.deeplearning4j.nn.conf.layers.BatchNormalization.Builder
-
- garbageCollection() - Method in class org.deeplearning4j.ui.stats.sbe.UpdateFieldsPresentDecoder
-
- garbageCollection(boolean) - Method in class org.deeplearning4j.ui.stats.sbe.UpdateFieldsPresentEncoder
-
- gateActivationFn - Variable in class org.deeplearning4j.nn.conf.layers.AbstractLSTM.Builder
-
- gateActivationFn - Variable in class org.deeplearning4j.nn.conf.layers.AbstractLSTM
-
- gateActivationFunction(String) - Method in class org.deeplearning4j.nn.conf.layers.AbstractLSTM.Builder
-
Activation function for the LSTM gates.
- gateActivationFunction(Activation) - Method in class org.deeplearning4j.nn.conf.layers.AbstractLSTM.Builder
-
Activation function for the LSTM gates.
- gateActivationFunction(IActivation) - Method in class org.deeplearning4j.nn.conf.layers.AbstractLSTM.Builder
-
Activation function for the LSTM gates.
- gateActivationFunction(String) - Method in class org.deeplearning4j.nn.conf.layers.GravesBidirectionalLSTM.Builder
-
Deprecated.
Activation function for the LSTM gates.
- gateActivationFunction(Activation) - Method in class org.deeplearning4j.nn.conf.layers.GravesBidirectionalLSTM.Builder
-
Deprecated.
Activation function for the LSTM gates.
- gateActivationFunction(IActivation) - Method in class org.deeplearning4j.nn.conf.layers.GravesBidirectionalLSTM.Builder
-
Deprecated.
Activation function for the LSTM gates.
- GaussianDistribution - Class in org.deeplearning4j.nn.conf.distribution
-
A normal distribution.
- GaussianDistribution(double, double) - Constructor for class org.deeplearning4j.nn.conf.distribution.GaussianDistribution
-
Create a gaussian distribution (equivalent to normal)
with the given mean and std
- GaussianDropout - Class in org.deeplearning4j.nn.conf.dropout
-
Gaussian dropout.
- GaussianDropout(double) - Constructor for class org.deeplearning4j.nn.conf.dropout.GaussianDropout
-
- GaussianDropout(ISchedule) - Constructor for class org.deeplearning4j.nn.conf.dropout.GaussianDropout
-
- GaussianDropout(double, ISchedule) - Constructor for class org.deeplearning4j.nn.conf.dropout.GaussianDropout
-
- GaussianNoise - Class in org.deeplearning4j.nn.conf.dropout
-
Applies additive, mean-zero Gaussian noise to the input - i.e., x = x + N(0,stddev).
Note that this differs from
GaussianDropout, which applies
multiplicative mean-1 N(1,s) noise.
Note also that schedules for the standard deviation value can also be used.
- GaussianNoise(double) - Constructor for class org.deeplearning4j.nn.conf.dropout.GaussianNoise
-
- GaussianNoise(ISchedule) - Constructor for class org.deeplearning4j.nn.conf.dropout.GaussianNoise
-
- GaussianNoise(double, ISchedule) - Constructor for class org.deeplearning4j.nn.conf.dropout.GaussianNoise
-
- GaussianReconstructionDistribution - Class in org.deeplearning4j.nn.conf.layers.variational
-
Gaussian reconstruction distribution for variational autoencoder.
Outputs are modelled by a Gaussian distribution, with the mean and variances (diagonal covariance matrix) for each
output determined by the network forward pass.
- GaussianReconstructionDistribution() - Constructor for class org.deeplearning4j.nn.conf.layers.variational.GaussianReconstructionDistribution
-
Create a GaussianReconstructionDistribution with the default identity activation function.
- GaussianReconstructionDistribution(Activation) - Constructor for class org.deeplearning4j.nn.conf.layers.variational.GaussianReconstructionDistribution
-
- GaussianReconstructionDistribution(IActivation) - Constructor for class org.deeplearning4j.nn.conf.layers.variational.GaussianReconstructionDistribution
-
- gcName() - Method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder.GcStatsDecoder
-
- gcName(String) - Method in class org.deeplearning4j.ui.stats.sbe.UpdateEncoder.GcStatsEncoder
-
- gcNameCharacterEncoding() - Static method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder.GcStatsDecoder
-
- gcNameCharacterEncoding() - Static method in class org.deeplearning4j.ui.stats.sbe.UpdateEncoder.GcStatsEncoder
-
- gcNameHeaderLength() - Static method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder.GcStatsDecoder
-
- gcNameHeaderLength() - Static method in class org.deeplearning4j.ui.stats.sbe.UpdateEncoder.GcStatsEncoder
-
- gcNameId() - Static method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder.GcStatsDecoder
-
- gcNameId() - Static method in class org.deeplearning4j.ui.stats.sbe.UpdateEncoder.GcStatsEncoder
-
- gcNameLength() - Method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder.GcStatsDecoder
-
- gcNameMetaAttribute(MetaAttribute) - Static method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder.GcStatsDecoder
-
- gcNameMetaAttribute(MetaAttribute) - Static method in class org.deeplearning4j.ui.stats.sbe.UpdateEncoder.GcStatsEncoder
-
- gcStats() - Method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder
-
- gcStatsCount(int) - Method in class org.deeplearning4j.ui.stats.sbe.UpdateEncoder
-
- GcStatsDecoder() - Constructor for class org.deeplearning4j.ui.stats.sbe.UpdateDecoder.GcStatsDecoder
-
- gcStatsDecoderId() - Static method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder
-
- GcStatsEncoder() - Constructor for class org.deeplearning4j.ui.stats.sbe.UpdateEncoder.GcStatsEncoder
-
- gcStatsId() - Static method in class org.deeplearning4j.ui.stats.sbe.UpdateEncoder
-
- gen - Variable in class org.deeplearning4j.models.embeddings.inmemory.InMemoryLookupTable.Builder
-
- gen(Random) - Method in class org.deeplearning4j.models.embeddings.inmemory.InMemoryLookupTable.Builder
-
- gen(Random) - Method in class org.deeplearning4j.models.glove.GloveWeightLookupTable.Builder
-
Deprecated.
- gen(Random) - Method in class org.deeplearning4j.spark.models.embeddings.glove.GloveParam.Builder
-
- generalValidation(String, Layer, IDropout, Double, Double, Double, Double, Distribution, List<LayerConstraint>, List<LayerConstraint>, List<LayerConstraint>) - Static method in class org.deeplearning4j.nn.conf.layers.LayerValidation
-
- generalValidation(String, Layer, IDropout, double, double, double, double, Distribution, List<LayerConstraint>, List<LayerConstraint>, List<LayerConstraint>) - Static method in class org.deeplearning4j.nn.conf.layers.LayerValidation
-
- generateAtMean(INDArray) - Method in class org.deeplearning4j.nn.conf.layers.variational.BernoulliReconstructionDistribution
-
- generateAtMean(INDArray) - Method in class org.deeplearning4j.nn.conf.layers.variational.CompositeReconstructionDistribution
-
- generateAtMean(INDArray) - Method in class org.deeplearning4j.nn.conf.layers.variational.ExponentialReconstructionDistribution
-
- generateAtMean(INDArray) - Method in class org.deeplearning4j.nn.conf.layers.variational.GaussianReconstructionDistribution
-
- generateAtMean(INDArray) - Method in class org.deeplearning4j.nn.conf.layers.variational.LossFunctionWrapper
-
- generateAtMean(INDArray) - Method in interface org.deeplearning4j.nn.conf.layers.variational.ReconstructionDistribution
-
Generate a sample from P(x|z), where x = E[P(x|z)]
i.e., return the mean value for the distribution
- generateAtMeanGivenZ(INDArray) - Method in class org.deeplearning4j.nn.layers.variational.VariationalAutoencoder
-
Given a specified values for the latent space as input (latent space being z in p(z|data)), generate output
from P(x|z), where x = E[P(x|z)]
i.e., return the mean value for the distribution P(x|z)
- generateGenericDictionaryEntry(T) - Method in class com.atilika.kuromoji.compile.TokenInfoDictionaryCompilerBase
-
- generateGenericDictionaryEntry(DictionaryEntry) - Method in class com.atilika.kuromoji.ipadic.compile.TokenInfoDictionaryCompiler
-
- generateRandom(INDArray) - Method in class org.deeplearning4j.nn.conf.layers.variational.BernoulliReconstructionDistribution
-
- generateRandom(INDArray) - Method in class org.deeplearning4j.nn.conf.layers.variational.CompositeReconstructionDistribution
-
- generateRandom(INDArray) - Method in class org.deeplearning4j.nn.conf.layers.variational.ExponentialReconstructionDistribution
-
- generateRandom(INDArray) - Method in class org.deeplearning4j.nn.conf.layers.variational.GaussianReconstructionDistribution
-
- generateRandom(INDArray) - Method in class org.deeplearning4j.nn.conf.layers.variational.LossFunctionWrapper
-
- generateRandom(INDArray) - Method in interface org.deeplearning4j.nn.conf.layers.variational.ReconstructionDistribution
-
Randomly sample from P(x|z) using the specified distribution parameters
- generateRandomGivenZ(INDArray, LayerWorkspaceMgr) - Method in class org.deeplearning4j.nn.layers.variational.VariationalAutoencoder
-
Given a specified values for the latent space as input (latent space being z in p(z|data)), randomly generate output
x, where x ~ P(x|z)
- generateUniform(int) - Static method in class org.deeplearning4j.clustering.util.MathUtils
-
This will generate a series of uniformally distributed
numbers between l times
- generator - Variable in class org.deeplearning4j.text.documentiterator.BasicLabelAwareIterator
-
- generator - Variable in class org.deeplearning4j.text.documentiterator.interoperability.DocumentIteratorConverter
-
- GenericDictionaryEntry - Class in com.atilika.kuromoji.dict
-
- GenericDictionaryEntry(GenericDictionaryEntry.Builder) - Constructor for class com.atilika.kuromoji.dict.GenericDictionaryEntry
-
- GenericDictionaryEntry.Builder - Class in com.atilika.kuromoji.dict
-
- GenericExceptionMapper - Class in org.deeplearning4j.ui.exception
-
- GenericExceptionMapper() - Constructor for class org.deeplearning4j.ui.exception.GenericExceptionMapper
-
- get(int) - Method in class com.atilika.kuromoji.buffer.StringValueMapBuffer
-
- get(int, int) - Method in class com.atilika.kuromoji.dict.ConnectionCosts
-
- get(Object) - Method in class com.atilika.kuromoji.trie.PatriciaTrie
-
Get value associated with specified key in this trie
- get(int) - Method in class org.ansj.domain.Result
-
- get() - Static method in class org.ansj.library.AmbiguityLibrary
-
获取系统默认词典
- get(String) - Static method in class org.ansj.library.AmbiguityLibrary
-
根据key获取
- get() - Static method in class org.ansj.library.CrfLibrary
-
- get(String) - Static method in class org.ansj.library.CrfLibrary
-
根据key获取crf分词器
- get() - Static method in class org.ansj.library.DicLibrary
-
- get(String) - Static method in class org.ansj.library.DicLibrary
-
根据模型名称获取crf模型
- get() - Static method in class org.ansj.library.StopLibrary
-
- get(String) - Static method in class org.ansj.library.StopLibrary
-
根据模型名称获取crf模型
- get() - Static method in class org.ansj.library.SynonymsLibrary
-
- get(String) - Static method in class org.ansj.library.SynonymsLibrary
-
- get(int) - Method in class org.deeplearning4j.datasets.iterator.parallel.MultiBoolean
-
Gets current state for specified entry
- get() - Method in class org.deeplearning4j.models.glove.count.RoundCount
-
- get(Integer) - Static method in class org.deeplearning4j.nn.modelimport.keras.config.KerasLayerConfigurationFactory
-
- get(short) - Static method in enum org.deeplearning4j.ui.stats.sbe.MemoryType
-
- get(short) - Static method in enum org.deeplearning4j.ui.stats.sbe.StatSource
-
- get(short) - Static method in enum org.deeplearning4j.ui.stats.sbe.StatsType
-
- get(short) - Static method in enum org.deeplearning4j.ui.stats.sbe.StatType
-
- get(short) - Static method in enum org.deeplearning4j.ui.stats.sbe.SummaryType
-
- get0(INDArray[]) - Static method in class org.deeplearning4j.earlystopping.scorecalc.base.BaseScoreCalculator
-
- get3DOutputSize(INDArray, int[], int[], int[], ConvolutionMode, int[], boolean) - Static method in class org.deeplearning4j.util.Convolution3DUtils
-
Get the output size (depth/height/width) for the given input data and CNN3D configuration
- get3DSameModeTopLeftPadding(int[], int[], int[], int[], int[]) - Static method in class org.deeplearning4j.util.Convolution3DUtils
-
Get top and left padding for same mode only for 3d convolutions
- getActivationFromConfig(Map<String, Object>, KerasLayerConfiguration) - Static method in class org.deeplearning4j.nn.modelimport.keras.utils.KerasActivationUtils
-
Get activation function from Keras layer configuration.
- getActivationLayer() - Method in class org.deeplearning4j.nn.modelimport.keras.layers.advanced.activations.KerasLeakyReLU
-
Get DL4J ActivationLayer.
- getActivationLayer() - Method in class org.deeplearning4j.nn.modelimport.keras.layers.core.KerasActivation
-
Get DL4J ActivationLayer.
- getActualTotal(T) - Method in class org.deeplearning4j.eval.ConfusionMatrix
-
Computes the total number of times the class actually appeared in the data.
- getAddress() - Method in class org.deeplearning4j.ui.api.UIServer
-
Get the address of the UI
- getAddress() - Method in class org.deeplearning4j.ui.play.PlayUIServer
-
- getAllCandidates(INDArray) - Method in class org.deeplearning4j.clustering.randomprojection.RPForest
-
Get all candidates relative to a specific datapoint.
- getAllCandidates(INDArray, List<RPTree>, String) - Static method in class org.deeplearning4j.clustering.randomprojection.RPUtils
-
Get the search candidates as indices given the input
and similarity function
- getAllFeatures(int) - Method in interface com.atilika.kuromoji.dict.Dictionary
-
Gets all features of the specified word id
- getAllFeatures(int) - Method in class com.atilika.kuromoji.dict.InsertedDictionary
-
- getAllFeatures(int) - Method in class com.atilika.kuromoji.dict.TokenInfoDictionary
-
- getAllFeatures(int) - Method in class com.atilika.kuromoji.dict.UnknownDictionary
-
- getAllFeatures(int) - Method in class com.atilika.kuromoji.dict.UserDictionary
-
- getAllFeatures() - Method in class com.atilika.kuromoji.TokenBase
-
Gets all features for this token as a comma-separated String
- getAllFeaturesArray(int) - Method in interface com.atilika.kuromoji.dict.Dictionary
-
Gets all features of the specified word id as a String array
- getAllFeaturesArray(int) - Method in class com.atilika.kuromoji.dict.InsertedDictionary
-
- getAllFeaturesArray(int) - Method in class com.atilika.kuromoji.dict.TokenInfoDictionary
-
- getAllFeaturesArray(int) - Method in class com.atilika.kuromoji.dict.UnknownDictionary
-
- getAllFeaturesArray(int) - Method in class com.atilika.kuromoji.dict.UserDictionary
-
- getAllFeaturesArray() - Method in class com.atilika.kuromoji.TokenBase
-
Gets all features for this token as a String array
- getAllFields(Class<?>) - Static method in class org.deeplearning4j.util.Dl4jReflection
-
- getAllFreq() - Method in class org.ansj.domain.NewWord
-
- getAllStaticInfos(String, String) - Method in interface org.deeplearning4j.api.storage.StatsStorage
-
Get all static informations for the given session and type ID
- getAllStaticInfos(String, String) - Method in class org.deeplearning4j.ui.storage.BaseCollectionStatsStorage
-
- getAllStaticInfos(String, String) - Method in class org.deeplearning4j.ui.storage.sqlite.J7FileStatsStorage
-
- getAllUpdatesAfter(String, String, String, long) - Method in interface org.deeplearning4j.api.storage.StatsStorage
-
Get all updates for the given session and worker ID, that occur after (not including) the given timestamp.
- getAllUpdatesAfter(String, String, long) - Method in interface org.deeplearning4j.api.storage.StatsStorage
-
Get all updates for the given session ID (all worker IDs), that occur after (not including) the given timestamp.
- getAllUpdatesAfter(String, String, String, long) - Method in class org.deeplearning4j.ui.storage.BaseCollectionStatsStorage
-
- getAllUpdatesAfter(String, String, long) - Method in class org.deeplearning4j.ui.storage.BaseCollectionStatsStorage
-
- getAllUpdatesAfter(String, String, String, long) - Method in class org.deeplearning4j.ui.storage.sqlite.J7FileStatsStorage
-
- getAllUpdatesAfter(String, String, long) - Method in class org.deeplearning4j.ui.storage.sqlite.J7FileStatsStorage
-
- getAllUpdateTimes(String, String, String) - Method in interface org.deeplearning4j.api.storage.StatsStorage
-
List the times of all updates for the specified sessionID, typeID and workerID
- getAllUpdateTimes(String, String, String) - Method in class org.deeplearning4j.ui.storage.BaseCollectionStatsStorage
-
- getAllUpdateTimes(String, String, String) - Method in class org.deeplearning4j.ui.storage.sqlite.J7FileStatsStorage
-
- getAlpha() - Method in class org.deeplearning4j.nn.conf.layers.CenterLossOutputLayer
-
- getAlpha() - Method in class org.deeplearning4j.spark.models.embeddings.word2vec.Word2VecParam
-
Deprecated.
- getAlpha() - Method in class org.deeplearning4j.spark.models.embeddings.word2vec.Word2VecPerformerVoid
-
Deprecated.
- getAlphaDropoutLayer() - Method in class org.deeplearning4j.nn.modelimport.keras.layers.noise.KerasAlphaDropout
-
Get DL4J DropoutLayer with Alpha dropout.
- getAmbiguityForest() - Method in class org.ansj.splitWord.Analysis
-
- getAnalysisEngine() - Method in class org.deeplearning4j.text.uima.UimaResource
-
- getArray() - Method in class com.atilika.kuromoji.compile.WordIdMapCompiler.GrowableIntArray
-
- getArrays() - Method in class org.deeplearning4j.streaming.kafka.NDArrayConsumer
-
Receive an ndarray from the queue
- getArraysReader() - Static method in class org.ansj.util.MyStaticValue
-
核心词典
- getAtrousConvolution1D() - Method in class org.deeplearning4j.nn.modelimport.keras.layers.convolutional.KerasAtrousConvolution1D
-
Get DL4J ConvolutionLayer.
- getAtrousConvolution2D() - Method in class org.deeplearning4j.nn.modelimport.keras.layers.convolutional.KerasAtrousConvolution2D
-
Get DL4J ConvolutionLayer.
- getAveragePointDistanceFromClusterCenter() - Method in class org.deeplearning4j.clustering.info.ClusterSetInfo
-
- getBaseBuffer() - Method in class com.atilika.kuromoji.trie.DoubleArrayTrie
-
- getBaseDir() - Method in class org.deeplearning4j.base.MnistFetcher
-
- getBaseDirForRDD(JavaRDD<?>) - Method in class org.deeplearning4j.spark.impl.paramavg.BaseTrainingMaster
-
- getBaseForm() - Method in class com.atilika.kuromoji.ipadic.compile.DictionaryEntry
-
- getBaseForm() - Method in class com.atilika.kuromoji.ipadic.Token
-
Gets the base form (also called dictionary form) for this token (基本形)
- getBatch() - Method in class org.deeplearning4j.models.embeddings.learning.impl.elements.CBOW
-
- getBatch() - Method in class org.deeplearning4j.models.embeddings.learning.impl.elements.SkipGram
-
- getBatch() - Method in class org.deeplearning4j.models.word2vec.iterator.Word2VecDataFetcher
-
- getBatchNormalizationLayer() - Method in class org.deeplearning4j.nn.modelimport.keras.layers.normalization.KerasBatchNormalization
-
Get DL4J BatchNormalizationLayer.
- getBegin() - Static method in class org.deeplearning4j.models.word2vec.iterator.Word2VecDataFetcher
-
- getBegin() - Method in class org.deeplearning4j.nn.layers.feedforward.autoencoder.recursive.Tree
-
- getBegin() - Method in class org.deeplearning4j.text.movingwindow.Window
-
- getBestModel() - Method in interface org.deeplearning4j.earlystopping.EarlyStoppingModelSaver
-
Retrieve the best model that was previously saved
- getBestModel() - Method in class org.deeplearning4j.earlystopping.EarlyStoppingResult
-
- getBestModel() - Method in class org.deeplearning4j.earlystopping.saver.InMemoryModelSaver
-
- getBestModel() - Method in class org.deeplearning4j.earlystopping.saver.LocalFileGraphSaver
-
- getBestModel() - Method in class org.deeplearning4j.earlystopping.saver.LocalFileModelSaver
-
- getBias() - Method in class org.deeplearning4j.models.glove.GloveWeightLookupTable
-
Deprecated.
- getBiasAdaGrad() - Method in class org.deeplearning4j.models.glove.GloveWeightLookupTable
-
Deprecated.
- getBiasL1RegularizationFromConfig(Map<String, Object>, boolean, KerasLayerConfiguration) - Static method in class org.deeplearning4j.nn.modelimport.keras.utils.KerasLayerUtils
-
Get L1 bias regularization (if any) from Keras bias regularization configuration.
- getBiasParameterKeys() - Method in class org.deeplearning4j.nn.conf.layers.samediff.SDLayerParams
-
- getBidirectionalLayer() - Method in class org.deeplearning4j.nn.modelimport.keras.layers.wrappers.KerasBidirectional
-
Get DL4J Bidirectional layer.
- getBinCounts() - Method in class org.deeplearning4j.eval.curves.BaseHistogram
-
- getBinLowerBounds() - Method in class org.deeplearning4j.eval.curves.BaseHistogram
-
- getBinLowerBounds() - Method in class org.deeplearning4j.eval.curves.Histogram
-
- getBinMidValues() - Method in class org.deeplearning4j.eval.curves.BaseHistogram
-
- getBinMidValues() - Method in class org.deeplearning4j.eval.curves.Histogram
-
- getBinUpperBounds() - Method in class org.deeplearning4j.eval.curves.BaseHistogram
-
- getBinUpperBounds() - Method in class org.deeplearning4j.eval.curves.Histogram
-
- getBit() - Method in class com.atilika.kuromoji.trie.PatriciaTrie.PatriciaNode
-
Returns this node's critical bit index
- getBottomRightXY() - Method in class org.deeplearning4j.nn.layers.objdetect.DetectedObject
-
Get the bottom right X/Y coordinates of the detected object
- getBoundary() - Method in class org.deeplearning4j.clustering.quadtree.QuadTree
-
- getBoundary() - Method in class org.deeplearning4j.clustering.sptree.SpTree
-
- getBoxesCreated() - Method in class org.deeplearning4j.aws.ec2.Ec2BoxCreator
-
- getBroadcastDims(int[], int) - Static method in class org.deeplearning4j.nn.conf.constraint.BaseConstraint
-
- getBroadCastVocabCache() - Method in class org.deeplearning4j.spark.text.functions.TextPipeline
-
- getBufferEntries() - Method in class com.atilika.kuromoji.compile.TokenInfoDictionaryCompilerBase
-
Deprecated.
- getBytesPerElement(DataBuffer.Type) - Method in class org.deeplearning4j.nn.conf.memory.MemoryReport
-
- getCache() - Method in class org.deeplearning4j.models.word2vec.iterator.Word2VecDataFetcher
-
- getCallbackTypeIDs() - Method in interface org.deeplearning4j.ui.api.UIModule
-
- getCallbackTypeIDs() - Method in class org.deeplearning4j.ui.module.convolutional.ConvolutionalListenerModule
-
- getCallbackTypeIDs() - Method in class org.deeplearning4j.ui.module.defaultModule.DefaultModule
-
- getCallbackTypeIDs() - Method in class org.deeplearning4j.ui.module.remote.RemoteReceiverModule
-
- getCallbackTypeIDs() - Method in class org.deeplearning4j.ui.module.train.TrainModule
-
- getCallbackTypeIDs() - Method in class org.deeplearning4j.ui.module.tsne.TsneModule
-
- getCandidates(INDArray) - Method in class org.deeplearning4j.clustering.randomprojection.RPTree
-
- getCandidates(INDArray, List<RPTree>, String) - Static method in class org.deeplearning4j.clustering.randomprojection.RPUtils
-
Get the search candidates as indices given the input
and similarity function
- getCardinality() - Method in class com.atilika.kuromoji.compile.ConnectionCostsCompiler
-
- getCasPool() - Method in class org.deeplearning4j.text.uima.UimaResource
-
- getCategoryDefinitions() - Method in class com.atilika.kuromoji.compile.CharacterDefinitionsCompiler
-
- getCenterOfMass() - Method in class org.deeplearning4j.clustering.quadtree.QuadTree
-
- getCenterOfMass() - Method in class org.deeplearning4j.clustering.sptree.SpTree
-
- getCharacterDefinition() - Method in class com.atilika.kuromoji.dict.UnknownDictionary
-
- getCheckBuffer() - Method in class com.atilika.kuromoji.trie.DoubleArrayTrie
-
- getChildren() - Method in class com.atilika.kuromoji.trie.Trie.Node
-
Returns this node's child nodes
- getChildren() - Method in class org.deeplearning4j.clustering.sptree.SpTree
-
- getChildren() - Method in class org.deeplearning4j.nn.layers.feedforward.autoencoder.recursive.Tree
-
- getClasses() - Method in class org.deeplearning4j.eval.ConfusionMatrix
-
Gives the applyTransformToDestination of all classes in the confusion matrix.
- getClassLabel(Integer) - Method in class org.deeplearning4j.eval.Evaluation
-
- getClassName() - Method in class org.deeplearning4j.nn.modelimport.keras.KerasLayer
-
Get Keras layer class name.
- getClassNameFromConfig(Map<String, Object>, KerasLayerConfiguration) - Static method in class org.deeplearning4j.nn.modelimport.keras.utils.KerasLayerUtils
-
Get Keras layer class name from Keras layer configuration.
- getClient() - Method in class org.deeplearning4j.aws.s3.BaseS3
-
- getCluster(String) - Method in class org.deeplearning4j.clustering.cluster.ClusterSet
-
- getClusterCenter(String) - Method in class org.deeplearning4j.clustering.cluster.ClusterSet
-
- getClusterCenterId(String) - Method in class org.deeplearning4j.clustering.cluster.ClusterSet
-
- getClusterCount() - Method in class org.deeplearning4j.clustering.cluster.ClusterSet
-
- getClusterInfo(String) - Method in class org.deeplearning4j.clustering.info.ClusterSetInfo
-
- getClusteringOptimizationValue() - Method in class org.deeplearning4j.clustering.strategy.OptimisationStrategy
-
- getClustersInfos() - Method in class org.deeplearning4j.clustering.info.ClusterSetInfo
-
- getClustersWhereAverageDistanceFromCenterGreaterThan(ClusterSet, ClusterSetInfo, double) - Static method in class org.deeplearning4j.clustering.cluster.ClusterUtils
-
- getClustersWhereMaximumDistanceFromCenterGreaterThan(ClusterSet, ClusterSetInfo, double) - Static method in class org.deeplearning4j.clustering.cluster.ClusterUtils
-
- getCode(int) - Method in interface org.deeplearning4j.graph.models.BinaryTree
-
- getCode(int) - Method in class org.deeplearning4j.graph.models.deepwalk.GraphHuffman
-
- getCode(int) - Method in interface org.deeplearning4j.models.sequencevectors.graph.huffman.BinaryTree
-
- getCode(int) - Method in class org.deeplearning4j.models.sequencevectors.graph.huffman.GraphHuffman
-
- getCodeLength(int) - Method in interface org.deeplearning4j.graph.models.BinaryTree
-
- getCodeLength(int) - Method in class org.deeplearning4j.graph.models.deepwalk.GraphHuffman
-
- getCodeLength(int) - Method in interface org.deeplearning4j.models.sequencevectors.graph.huffman.BinaryTree
-
- getCodeLength(int) - Method in class org.deeplearning4j.models.sequencevectors.graph.huffman.GraphHuffman
-
- getCodeLength() - Method in class org.deeplearning4j.models.sequencevectors.sequence.SequenceElement
-
Returns Huffman code length.
- getCodeList(int) - Method in class org.deeplearning4j.models.sequencevectors.graph.huffman.GraphHuffman
-
- getCodeName() - Method in interface org.deeplearning4j.models.embeddings.learning.ElementsLearningAlgorithm
-
- getCodeName() - Method in class org.deeplearning4j.models.embeddings.learning.impl.elements.CBOW
-
- getCodeName() - Method in class org.deeplearning4j.models.embeddings.learning.impl.elements.GloVe
-
- getCodeName() - Method in class org.deeplearning4j.models.embeddings.learning.impl.elements.SkipGram
-
Returns implementation code name
- getCodeName() - Method in class org.deeplearning4j.models.embeddings.learning.impl.sequence.DBOW
-
- getCodeName() - Method in class org.deeplearning4j.models.embeddings.learning.impl.sequence.DM
-
- getCodeName() - Method in interface org.deeplearning4j.models.embeddings.learning.SequenceLearningAlgorithm
-
- getCodeName() - Method in class org.deeplearning4j.spark.models.sequencevectors.learning.elements.SparkCBOW
-
- getCodeName() - Method in class org.deeplearning4j.spark.models.sequencevectors.learning.elements.SparkSkipGram
-
- getCodeName() - Method in class org.deeplearning4j.spark.models.sequencevectors.learning.sequence.SparkDBOW
-
- getCodeName() - Method in class org.deeplearning4j.spark.models.sequencevectors.learning.sequence.SparkDM
-
- getCodepointCategories() - Method in class com.atilika.kuromoji.compile.CharacterDefinitionsCompiler
-
- getCodes() - Method in class org.deeplearning4j.models.embeddings.inmemory.InMemoryLookupTable
-
- getCodes() - Method in class org.deeplearning4j.models.sequencevectors.sequence.SequenceElement
-
Returns Huffman tree codes
- getCodeString(int) - Method in interface org.deeplearning4j.graph.models.BinaryTree
-
- getCodeString(int) - Method in class org.deeplearning4j.graph.models.deepwalk.GraphHuffman
-
- getCodeString(int) - Method in interface org.deeplearning4j.models.sequencevectors.graph.huffman.BinaryTree
-
- getCodeString(int) - Method in class org.deeplearning4j.models.sequencevectors.graph.huffman.GraphHuffman
-
- getCols() - Method in class org.deeplearning4j.datasets.mnist.MnistImageFile
-
Number of columns per image.
- getCompanReader() - Static method in class org.ansj.util.MyStaticValue
-
机构名词典
- getCompanyMap() - Static method in class org.ansj.library.company.CompanyAttrLibrary
-
- getComputationGraph() - Method in class org.deeplearning4j.nn.modelimport.keras.KerasModel
-
Build a ComputationGraph from this Keras Model configuration and import weights.
- getComputationGraph(boolean) - Method in class org.deeplearning4j.nn.modelimport.keras.KerasModel
-
Build a ComputationGraph from this Keras Model configuration and (optionally) import weights.
- getComputationGraphConfiguration() - Method in class org.deeplearning4j.nn.modelimport.keras.KerasModel
-
Configure a ComputationGraph from this Keras Model configuration.
- getComputationGraphUpdater() - Method in interface org.deeplearning4j.optimize.api.ConvexOptimizer
-
- getComputationGraphUpdater() - Method in class org.deeplearning4j.optimize.solvers.BaseOptimizer
-
- getConf(int) - Method in class org.deeplearning4j.nn.conf.MultiLayerConfiguration
-
- getConf() - Method in interface org.deeplearning4j.optimize.api.ConvexOptimizer
-
- getConf() - Method in class org.deeplearning4j.optimize.solvers.BaseOptimizer
-
- getConf() - Method in class org.deeplearning4j.spark.datavec.iterator.SparkSourceDummyReader
-
- getConfidenceMatrix(INDArray, int, int) - Method in class org.deeplearning4j.nn.layers.objdetect.Yolo2OutputLayer
-
Get the confidence matrix (confidence for all x/y positions) for the specified bounding box, from the network
output activations array
- getConfig() - Method in class org.ansj.app.crf.Model
-
- getConfiguration() - Method in class org.deeplearning4j.nn.graph.ComputationGraph
-
This method returns configuration of this ComputationGraph
- getConfusionMatrix() - Method in class org.deeplearning4j.eval.Evaluation
-
Returns the confusion matrix variable
- getConfusionMatrixAtPoint(int) - Method in class org.deeplearning4j.eval.curves.PrecisionRecallCurve
-
Get the binary confusion matrix for the given position.
- getConfusionMatrixAtThreshold(double) - Method in class org.deeplearning4j.eval.curves.PrecisionRecallCurve
-
Get the binary confusion matrix for the given threshold.
- getConjugatedForm() - Method in class com.atilika.kuromoji.ipadic.compile.DictionaryEntry
-
- getConjugationForm() - Method in class com.atilika.kuromoji.ipadic.Token
-
Gets the conjugation form for this token (活用形), if applicable
- getConjugationType() - Method in class com.atilika.kuromoji.ipadic.compile.DictionaryEntry
-
- getConjugationType() - Method in class com.atilika.kuromoji.ipadic.Token
-
Gets the conjugation type for this token (活用型), if applicable
- getConnectedVertexIndices(int) - Method in interface org.deeplearning4j.graph.api.IGraph
-
Return an array of indexes of vertices that the specified vertex is connected to.
Specifically, for undirected graphs return int[] of all X.vertexID() such that (vertex -- X) exists
For directed graphs, return int[] of all X.vertexID() such that (vertex -> X) exists
- getConnectedVertexIndices(int) - Method in class org.deeplearning4j.graph.graph.Graph
-
- getConnectedVertexIndices(int) - Method in class org.deeplearning4j.models.sequencevectors.graph.primitives.Graph
-
- getConnectedVertexIndices(int) - Method in interface org.deeplearning4j.models.sequencevectors.graph.primitives.IGraph
-
Return an array of indexes of vertices that the specified vertex is connected to.
Specifically, for undirected graphs return int[] of all X.vertexID() such that (vertex -- X) exists
For directed graphs, return int[] of all X.vertexID() such that (vertex -> X) exists
- getConnectedVertices(int) - Method in interface org.deeplearning4j.graph.api.IGraph
-
Get a list of all of the vertices that the specified vertex is connected to
Specifically, for undirected graphs return list of all X such that (vertex -- X) exists
For directed graphs, return list of all X such that (vertex -> X) exists
- getConnectedVertices(int) - Method in class org.deeplearning4j.graph.graph.Graph
-
- getConnectedVertices(int) - Method in class org.deeplearning4j.models.sequencevectors.graph.primitives.Graph
-
- getConnectedVertices(int) - Method in interface org.deeplearning4j.models.sequencevectors.graph.primitives.IGraph
-
Get a list of all of the vertices that the specified vertex is connected to
Specifically, for undirected graphs return list of all X such that (vertex -- X) exists
For directed graphs, return list of all X such that (vertex -> X) exists
- getConstraintsFromConfig(Map<String, Object>, String, KerasLayerConfiguration, int) - Static method in class org.deeplearning4j.nn.modelimport.keras.utils.KerasConstraintUtils
-
Get constraint initialization from Keras layer configuration.
- getContext(Class<?>) - Method in class org.deeplearning4j.ui.providers.ObjectMapperProvider
-
- getConvolution1DLayer() - Method in class org.deeplearning4j.nn.modelimport.keras.layers.convolutional.KerasConvolution1D
-
Get DL4J ConvolutionLayer.
- getConvolution2DLayer() - Method in class org.deeplearning4j.nn.modelimport.keras.layers.convolutional.KerasConvolution2D
-
Get DL4J ConvolutionLayer.
- getConvolution3DLayer() - Method in class org.deeplearning4j.nn.modelimport.keras.layers.convolutional.KerasConvolution3D
-
Get DL4J ConvolutionLayer.
- getConvolutionModeFromConfig(Map<String, Object>, KerasLayerConfiguration) - Static method in class org.deeplearning4j.nn.modelimport.keras.layers.convolutional.KerasConvolutionUtils
-
Get convolution border mode from Keras layer configuration.
- getCoOccurrenceCount(T, T) - Method in class org.deeplearning4j.models.glove.AbstractCoOccurrences
-
This method returns cooccurrence distance weights for two SequenceElements
- getCoOccurrenceCounts() - Method in class org.deeplearning4j.spark.models.embeddings.glove.GloveParam
-
- getCorruptedInput(INDArray, double) - Method in class org.deeplearning4j.nn.layers.BasePretrainNetwork
-
Corrupts the given input by doing a binomial sampling
given the corruption level
- getCosts() - Method in class com.atilika.kuromoji.compile.ConnectionCostsCompiler
-
- getCount() - Method in class org.deeplearning4j.datasets.mnist.MnistDbFile
-
- getCount(T, T) - Method in class org.deeplearning4j.eval.ConfusionMatrix
-
Gives the count of the number of times the "predicted" class was predicted for the "actual"
class.
- getCount(T, T) - Method in class org.deeplearning4j.models.glove.count.CountMap
-
- getCount(Pair<T, T>) - Method in class org.deeplearning4j.models.glove.count.CountMap
-
- getCount() - Method in class org.deeplearning4j.models.word2vec.StreamWork
-
- getCount() - Method in class org.deeplearning4j.models.word2vec.VocabWork
-
- getCountActualNegative(int) - Method in class org.deeplearning4j.eval.ROCBinary
-
Get the actual negative count (accounting for any masking) for the specified output/column
- getCountActualNegative(int) - Method in class org.deeplearning4j.eval.ROCMultiClass
-
Get the actual negative count (accounting for any masking) for the specified output/column
- getCountActualPositive(int) - Method in class org.deeplearning4j.eval.ROCBinary
-
Get the actual positive count (accounting for any masking) for the specified output/column
- getCountActualPositive(int) - Method in class org.deeplearning4j.eval.ROCMultiClass
-
Get the actual positive count (accounting for any masking) for the specified class
- getCounter() - Method in class org.deeplearning4j.parallelism.inference.observers.BatchedInferenceObservable
-
- getCounter() - Method in class org.deeplearning4j.spark.models.sequencevectors.SparkSequenceVectors
-
- getCounter() - Method in class org.deeplearning4j.spark.parameterserver.networking.messages.SilentUpdatesMessage
-
- getCreds() - Method in class org.deeplearning4j.aws.s3.BaseS3
-
- getCropping1DLayer() - Method in class org.deeplearning4j.nn.modelimport.keras.layers.convolutional.KerasCropping1D
-
Get DL4J Cropping1D layer.
- getCropping2DLayer() - Method in class org.deeplearning4j.nn.modelimport.keras.layers.convolutional.KerasCropping2D
-
Get DL4J Cropping2D layer.
- getCropping3DLayer() - Method in class org.deeplearning4j.nn.modelimport.keras.layers.convolutional.KerasCropping3D
-
Get DL4J Cropping3D layer.
- getCsvFiles(File) - Method in class com.atilika.kuromoji.compile.TokenInfoDictionaryCompilerBase
-
- getCudnnForwardArgs(INDArray, int[], int[], int[], int[], ConvolutionMode) - Static method in class org.deeplearning4j.nn.layers.convolution.CudnnConvolutionHelper
-
- getCumSize() - Method in class org.deeplearning4j.clustering.quadtree.QuadTree
-
- getCumSize() - Method in class org.deeplearning4j.clustering.sptree.SpTree
-
- getCumSumRDD() - Method in class org.deeplearning4j.spark.text.functions.CountCumSum
-
- getCurrentIndex() - Method in class org.deeplearning4j.datasets.mnist.MnistDbFile
-
The current entry index.
- getCurrentProducerIndex() - Method in class org.deeplearning4j.datasets.iterator.parallel.BaseParallelDataSetIterator
-
- getD() - Method in class org.deeplearning4j.clustering.sptree.SpTree
-
- getData() - Method in class org.deeplearning4j.plot.BarnesHutTsne
-
Return the matrix reduce to the NDim.
- getDataConfiguration() - Method in interface org.deeplearning4j.spark.api.TrainingWorker
-
- getDataConfiguration() - Method in class org.deeplearning4j.spark.impl.paramavg.ParameterAveragingTrainingWorker
-
- getDataConfiguration() - Method in class org.deeplearning4j.spark.parameterserver.training.SharedTrainingWorker
-
- getDataSetMetaData() - Method in interface org.deeplearning4j.ui.stats.api.StatsReport
-
Get the DataSet metadata, if any (null otherwise).
- getDataSetMetaData() - Method in class org.deeplearning4j.ui.stats.impl.java.JavaStatsReport
-
- getDataSetMetaData() - Method in class org.deeplearning4j.ui.stats.impl.SbeStatsReport
-
- getDataSetMetaDataClassName() - Method in interface org.deeplearning4j.ui.stats.api.StatsReport
-
Get the class
- getDataSetMetaDataClassName() - Method in class org.deeplearning4j.ui.stats.impl.java.JavaStatsReport
-
- getDataSetMetaDataClassName() - Method in class org.deeplearning4j.ui.stats.impl.SbeStatsReport
-
- getDataSetMetaDataClassName(MutableDirectBuffer, int, int) - Method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder
-
- getDataSetMetaDataClassName(byte[], int, int) - Method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder
-
- getDataSetPath(DataSetType) - Method in class org.deeplearning4j.datasets.fetchers.SvhnDataFetcher
-
- getDataSets(String...) - Method in class org.deeplearning4j.nn.modelimport.keras.Hdf5Archive
-
Get list of data sets from group path.
- getDeconvolution2DLayer() - Method in class org.deeplearning4j.nn.modelimport.keras.layers.convolutional.KerasDeconvolution2D
-
Get DL4J ConvolutionLayer.
- getDeconvolutionOutputSize(INDArray, int[], int[], int[], ConvolutionMode, int[]) - Static method in class org.deeplearning4j.util.ConvolutionUtils
-
Get the output size of a deconvolution operation for given input data.
- getDefault(String) - Static method in class org.deeplearning4j.spark.models.embeddings.word2vec.Word2VecVariables
-
Deprecated.
- getDefaultConfiguration() - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
-
- getDefaultExportDirectory(SparkContext) - Method in class org.deeplearning4j.spark.impl.paramavg.BaseTrainingMaster
-
- getDefaultLanguage() - Method in interface org.deeplearning4j.ui.api.I18N
-
Get the currently set default language as an ISO 639-1 code
- getDefaultLanguage() - Method in class org.deeplearning4j.ui.i18n.DefaultI18N
-
- getDefaultStepFunctionForOptimizer(Class<? extends ConvexOptimizer>) - Static method in class org.deeplearning4j.optimize.solvers.BaseOptimizer
-
- getDenseLayer() - Method in class org.deeplearning4j.nn.modelimport.keras.layers.core.KerasDense
-
Get DL4J DenseLayer.
- getDepth() - Method in class org.deeplearning4j.nn.conf.inputs.InputType.InputTypeConvolutional
-
Deprecated.
- getDepthwiseConvolution2DLayer() - Method in class org.deeplearning4j.nn.modelimport.keras.layers.convolutional.KerasDepthwiseConvolution2D
-
Get DL4J DepthwiseConvolution2D.
- getDescription(String) - Static method in class org.deeplearning4j.text.annotator.PoStagger
-
- getDescription() - Static method in class org.deeplearning4j.text.annotator.SentenceAnnotator
-
- getDescription() - Static method in class org.deeplearning4j.text.annotator.StemmerAnnotator
-
- getDescription(String) - Static method in class org.deeplearning4j.text.annotator.StemmerAnnotator
-
- getDescription(String) - Static method in class org.deeplearning4j.text.annotator.TokenizerAnnotator
-
- getDescription() - Static method in class org.deeplearning4j.text.annotator.TokenizerAnnotator
-
- getDeserializedType() - Method in class org.deeplearning4j.nn.conf.serde.legacyformat.LegacyGraphVertexDeserializer
-
- getDeserializedType() - Method in class org.deeplearning4j.nn.conf.serde.legacyformat.LegacyLayerDeserializer
-
- getDeserializedType() - Method in class org.deeplearning4j.nn.conf.serde.legacyformat.LegacyPreprocessorDeserializer
-
- getDeserializedType() - Method in class org.deeplearning4j.nn.conf.serde.legacyformat.LegacyReconstructionDistributionDeserializer
-
- getDeviceCurrentBytes() - Method in interface org.deeplearning4j.ui.stats.api.StatsReport
-
Get device (GPU, etc) current bytes - may be null if no compute devices are present in the system
- getDeviceDescription(MutableDirectBuffer, int, int) - Method in class org.deeplearning4j.ui.stats.sbe.StaticInfoDecoder.HwDeviceInfoGroupDecoder
-
- getDeviceDescription(byte[], int, int) - Method in class org.deeplearning4j.ui.stats.sbe.StaticInfoDecoder.HwDeviceInfoGroupDecoder
-
- getDeviceMaxBytes() - Method in interface org.deeplearning4j.ui.stats.api.StatsReport
-
Get device (GPU, etc) maximum bytes - may be null if no compute devices are present in the system
- getDictionaryEntries() - Method in class com.atilika.kuromoji.compile.TokenInfoDictionaryCompilerBase
-
Deprecated.
- getDictionaryEntries() - Method in class com.atilika.kuromoji.compile.UnknownDictionaryCompiler
-
- getDimOrder() - Method in class org.deeplearning4j.nn.modelimport.keras.KerasLayer
-
Get Keras layer backend dimension order.
- getDimOrderFromConfig(Map<String, Object>, KerasLayerConfiguration) - Static method in class org.deeplearning4j.nn.modelimport.keras.utils.KerasLayerUtils
-
Get Keras (backend) dimension order from Keras layer configuration.
- getDistance(Point, Point) - Method in class org.deeplearning4j.clustering.cluster.ClusterSet
-
- getDistance() - Method in class org.deeplearning4j.clustering.sptree.HeapItem
-
- getDistanceFromNearestCluster(Point) - Method in class org.deeplearning4j.clustering.cluster.ClusterSet
-
- getDistanceFunction() - Method in interface org.deeplearning4j.clustering.strategy.ClusteringStrategy
-
- getDistanceMeasure() - Method in interface org.deeplearning4j.clustering.lsh.LSH
-
Returns an instance of the distance measure associated to the LSH family of this implementation.
- getDistanceMeasure() - Method in class org.deeplearning4j.clustering.lsh.RandomProjectionLSH
-
- getDistancesBetweenClustersCenters() - Method in class org.deeplearning4j.clustering.info.ClusterSetInfo
-
- getDistanceToCenter(Point) - Method in class org.deeplearning4j.clustering.cluster.Cluster
-
Get the distance to the given
point from the cluster
- getDropoutFromConfig(Map<String, Object>, KerasLayerConfiguration) - Static method in class org.deeplearning4j.nn.modelimport.keras.utils.KerasLayerUtils
-
Get dropout from Keras layer configuration.
- getDropoutLayer() - Method in class org.deeplearning4j.nn.modelimport.keras.layers.core.KerasDropout
-
Get DL4J DropoutLayer.
- getDurationAsString(List<EventStats>, String) - Static method in class org.deeplearning4j.spark.stats.StatsUtils
-
- getDurationMs() - Method in class org.deeplearning4j.spark.stats.BaseEventStats
-
- getDurationMs() - Method in interface org.deeplearning4j.spark.stats.EventStats
-
- getEc2() - Method in class org.deeplearning4j.aws.s3.BaseS3
-
- getEdgesOut(int) - Method in interface org.deeplearning4j.graph.api.IGraph
-
Returns a list of edges for a vertex with a given index
For undirected graphs, returns all edges incident on the vertex
For directed graphs, only returns outward directed edges
- getEdgesOut(int) - Method in class org.deeplearning4j.graph.graph.Graph
-
- getEdgesOut(int) - Method in class org.deeplearning4j.models.sequencevectors.graph.primitives.Graph
-
- getEdgesOut(int) - Method in interface org.deeplearning4j.models.sequencevectors.graph.primitives.IGraph
-
Returns a list of edges for a vertex with a given index
For undirected graphs, returns all edges incident on the vertex
For directed graphs, only returns outward directed edges
- getElementByIndex(int) - Method in class org.deeplearning4j.models.sequencevectors.sequence.Sequence
-
This method returns sequence element by index
- getElementByLabel(String) - Method in class org.deeplearning4j.models.sequencevectors.sequence.Sequence
-
Returns single element out of this sequence by its label
- getElementFrequency() - Method in class org.deeplearning4j.models.sequencevectors.sequence.SequenceElement
-
This method returns SequenceElement's frequency in current training corpus.
- getElements() - Method in class org.deeplearning4j.models.sequencevectors.sequence.Sequence
-
Returns an ordered unmodifiable list of elements from this sequence
- getElementsLearningAlgorithm() - Method in class org.deeplearning4j.models.embeddings.learning.impl.sequence.DBOW
-
- getElementsLearningAlgorithm() - Method in class org.deeplearning4j.models.embeddings.learning.impl.sequence.DM
-
- getElementsLearningAlgorithm() - Method in interface org.deeplearning4j.models.embeddings.learning.SequenceLearningAlgorithm
-
- getElementsLearningAlgorithm() - Method in class org.deeplearning4j.spark.models.sequencevectors.learning.sequence.BaseSparkSequenceLearningAlgorithm
-
- getElementsScore() - Method in class org.deeplearning4j.models.sequencevectors.SequenceVectors
-
- getEmbeddingLayer() - Method in class org.deeplearning4j.nn.modelimport.keras.layers.embeddings.KerasEmbedding
-
Get DL4J Embedding Sequence layer.
- getEmptyConstructor(Class<?>) - Static method in class org.deeplearning4j.util.Dl4jReflection
-
Gets the empty constructor from a class
- getEn(String) - Static method in class org.ansj.app.crf.Config
-
- getEnd() - Static method in class org.deeplearning4j.models.word2vec.iterator.Word2VecDataFetcher
-
- getEnd() - Method in class org.deeplearning4j.nn.layers.feedforward.autoencoder.recursive.Tree
-
- getEnd() - Method in class org.deeplearning4j.text.movingwindow.Window
-
- getEndIndexArr() - Method in class com.atilika.kuromoji.viterbi.ViterbiLattice
-
- getEndSizeArr() - Method in class com.atilika.kuromoji.viterbi.ViterbiLattice
-
- getEnglishReader() - Static method in class org.ansj.util.MyStaticValue
-
英文词典
- getEntryCount() - Method in class com.atilika.kuromoji.buffer.FeatureInfoMap
-
- getEntryIndices(String) - Method in class com.atilika.kuromoji.compile.UnknownDictionaryCompiler
-
- getEntryLength() - Method in class org.deeplearning4j.datasets.mnist.MnistDbFile
-
Number of bytes for each entry.
- getEntryLength() - Method in class org.deeplearning4j.datasets.mnist.MnistImageFile
-
- getEnvKey(MutableDirectBuffer, int, int) - Method in class org.deeplearning4j.ui.stats.sbe.StaticInfoDecoder.SwEnvironmentInfoDecoder
-
- getEnvKey(byte[], int, int) - Method in class org.deeplearning4j.ui.stats.sbe.StaticInfoDecoder.SwEnvironmentInfoDecoder
-
- getEnvValue(MutableDirectBuffer, int, int) - Method in class org.deeplearning4j.ui.stats.sbe.StaticInfoDecoder.SwEnvironmentInfoDecoder
-
- getEnvValue(byte[], int, int) - Method in class org.deeplearning4j.ui.stats.sbe.StaticInfoDecoder.SwEnvironmentInfoDecoder
-
- getEpoch(Model) - Static method in class org.deeplearning4j.optimize.listeners.checkpoint.CheckpointListener
-
- getEpochCount() - Method in interface org.deeplearning4j.nn.api.Layer
-
- getEpochCount() - Method in class org.deeplearning4j.nn.layers.recurrent.BidirectionalLayer
-
- getEpochCount() - Method in class org.deeplearning4j.nn.layers.wrapper.BaseWrapperLayer
-
- getEpochCount() - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
-
- getEpochCount(Model) - Static method in class org.deeplearning4j.optimize.solvers.BaseOptimizer
-
- getEps() - Method in class org.deeplearning4j.nn.conf.layers.SubsamplingLayer
-
- getEpsilon() - Method in class org.deeplearning4j.nn.graph.vertex.BaseGraphVertex
-
- getEpsilon() - Method in class org.deeplearning4j.nn.graph.vertex.BaseWrapperVertex
-
- getEpsilon() - Method in interface org.deeplearning4j.nn.graph.vertex.GraphVertex
-
Get the epsilon/error (i.e., dL/dOutput) array previously set for this GraphVertex
- getError() - Method in class org.deeplearning4j.spark.models.embeddings.glove.GloveChange
-
- getExamplesPerSecond() - Method in interface org.deeplearning4j.ui.stats.api.StatsReport
-
Get examples per second since the last report
- getExpTable() - Method in class org.deeplearning4j.models.embeddings.inmemory.InMemoryLookupTable
-
- getExpTable() - Method in class org.deeplearning4j.spark.models.embeddings.word2vec.Word2VecParam
-
Deprecated.
- getExpTable() - Method in class org.deeplearning4j.spark.models.embeddings.word2vec.Word2VecPerformerVoid
-
Deprecated.
- getExtraMetaData() - Method in interface org.deeplearning4j.api.storage.StorageMetaData
-
Get extra metadata, if any
- getExtraMetaData() - Method in class org.deeplearning4j.ui.storage.impl.JavaStorageMetaData
-
- getExtraMetaData() - Method in class org.deeplearning4j.ui.storage.impl.SbeStorageMetaData
-
- getFalsePositiveRate(int) - Method in class org.deeplearning4j.eval.curves.RocCurve
-
- getFeature(int, int...) - Method in interface com.atilika.kuromoji.dict.Dictionary
-
Gets one or more specific features of a token
- getFeature(int, int...) - Method in class com.atilika.kuromoji.dict.InsertedDictionary
-
- getFeature(int, int...) - Method in class com.atilika.kuromoji.dict.TokenInfoDictionary
-
- getFeature(int, int...) - Method in class com.atilika.kuromoji.dict.UnknownDictionary
-
- getFeature(int, int...) - Method in class com.atilika.kuromoji.dict.UserDictionary
-
- getFeature(int) - Method in class com.atilika.kuromoji.TokenBase
-
Gets a numbered feature for this token
- getFeature(char...) - Method in class org.ansj.app.crf.Model
-
获得特征所在权重数组
- getFeatures() - Method in class com.atilika.kuromoji.dict.GenericDictionaryEntry
-
- getFieldsAsProperties(Object, Class<?>[]) - Static method in class org.deeplearning4j.util.Dl4jReflection
-
Get fields as properties
- getFileForCheckpoint(Checkpoint) - Method in class org.deeplearning4j.optimize.listeners.checkpoint.CheckpointListener
-
Get the model file for the given checkpoint.
- getFileForCheckpoint(int) - Method in class org.deeplearning4j.optimize.listeners.checkpoint.CheckpointListener
-
Get the model file for the given checkpoint number.
- getFileHeader() - Static method in class org.deeplearning4j.optimize.listeners.checkpoint.Checkpoint
-
- getFiles() - Method in class org.deeplearning4j.models.word2vec.iterator.Word2VecDataFetcher
-
- getFinalResult(MultiLayerNetwork) - Method in interface org.deeplearning4j.spark.api.TrainingWorker
-
Get the final result to be returned to the driver
- getFinalResult(ComputationGraph) - Method in interface org.deeplearning4j.spark.api.TrainingWorker
-
Get the final result to be returned to the driver
- getFinalResult(MultiLayerNetwork) - Method in class org.deeplearning4j.spark.impl.paramavg.ParameterAveragingTrainingWorker
-
- getFinalResult(ComputationGraph) - Method in class org.deeplearning4j.spark.impl.paramavg.ParameterAveragingTrainingWorker
-
- getFinalResult(MultiLayerNetwork) - Method in class org.deeplearning4j.spark.parameterserver.training.SharedTrainingWorker
-
- getFinalResult(ComputationGraph) - Method in class org.deeplearning4j.spark.parameterserver.training.SharedTrainingWorker
-
- getFinalResultNoData() - Method in interface org.deeplearning4j.spark.api.TrainingWorker
-
Get the final result to be returned to the driver, if no data was available for this executor
- getFinalResultNoData() - Method in class org.deeplearning4j.spark.impl.paramavg.ParameterAveragingTrainingWorker
-
- getFinalResultNoData() - Method in class org.deeplearning4j.spark.parameterserver.training.SharedTrainingWorker
-
- getFinalResultNoDataWithStats() - Method in interface org.deeplearning4j.spark.api.TrainingWorker
-
- getFinalResultNoDataWithStats() - Method in class org.deeplearning4j.spark.impl.paramavg.ParameterAveragingTrainingWorker
-
- getFinalResultNoDataWithStats() - Method in class org.deeplearning4j.spark.parameterserver.training.SharedTrainingWorker
-
- getFinalResultWithStats(MultiLayerNetwork) - Method in interface org.deeplearning4j.spark.api.TrainingWorker
-
- getFinalResultWithStats(ComputationGraph) - Method in interface org.deeplearning4j.spark.api.TrainingWorker
-
- getFinalResultWithStats(MultiLayerNetwork) - Method in class org.deeplearning4j.spark.impl.paramavg.ParameterAveragingTrainingWorker
-
- getFinalResultWithStats(ComputationGraph) - Method in class org.deeplearning4j.spark.impl.paramavg.ParameterAveragingTrainingWorker
-
- getFinalResultWithStats(MultiLayerNetwork) - Method in class org.deeplearning4j.spark.parameterserver.training.SharedTrainingWorker
-
- getFinalResultWithStats(ComputationGraph) - Method in class org.deeplearning4j.spark.parameterserver.training.SharedTrainingWorker
-
- getFirstPart() - Method in class org.deeplearning4j.ui.UiConnectionInfo
-
This method returns scheme, address and port for this UiConnectionInfo
i.e: https://localhost:8080
- getFlattenedGradientsView() - Method in class org.deeplearning4j.nn.updater.BaseMultiLayerUpdater
-
- getFlattenedGradientsView() - Method in class org.deeplearning4j.nn.updater.graph.ComputationGraphUpdater
-
- getFlattenedGradientsView() - Method in class org.deeplearning4j.nn.updater.LayerUpdater
-
- getFlattenedGradientsView() - Method in class org.deeplearning4j.nn.updater.MultiLayerUpdater
-
- getFlattenedSize() - Method in class org.deeplearning4j.nn.conf.inputs.InputType.InputTypeConvolutionalFlat
-
- getFloat(byte[]) - Static method in class org.deeplearning4j.models.embeddings.loader.WordVectorSerializer
-
Read a string from a data input stream Credit to:
https://github.com/NLPchina/Word2VEC_java/blob/master/src/com/ansj/vec/Word2VEC.java
- getFocusWord() - Method in class org.deeplearning4j.text.movingwindow.Window
-
- getForest() - Method in class org.ansj.dic.LearnTool
-
- getForgetBiasInitFromConfig(Map<String, Object>, boolean) - Method in class org.deeplearning4j.nn.modelimport.keras.layers.recurrent.KerasLstm
-
Get LSTM forget gate bias initialization from Keras layer configuration.
- getFrameId() - Method in class org.deeplearning4j.spark.parameterserver.networking.messages.SilentUpdatesMessage
-
- getFreq() - Method in class org.ansj.app.keyword.Keyword
-
- getFreq(int, int) - Method in class org.ansj.domain.PersonNatureAttr
-
得道某一个位置的词频
- getFullAddress(String) - Method in class org.deeplearning4j.ui.UiConnectionInfo
-
- getFullAddress() - Method in class org.deeplearning4j.ui.UiConnectionInfo
-
- getGain() - Method in class org.deeplearning4j.nn.conf.distribution.OrthogonalDistribution
-
- getGarbageCollectionStats() - Method in interface org.deeplearning4j.ui.stats.api.StatsReport
-
Get the garbage collection stats: Pair contains GC name and the delta count/time values
- getGarbageCollectionStats() - Method in class org.deeplearning4j.ui.stats.impl.java.JavaStatsReport
-
- getGarbageCollectionStats() - Method in class org.deeplearning4j.ui.stats.impl.SbeStatsReport
-
- getGateActivationFromConfig(Map<String, Object>) - Method in class org.deeplearning4j.nn.modelimport.keras.layers.recurrent.KerasLstm
-
Get LSTM gate activation function from Keras layer configuration.
- getGaussianDropoutLayer() - Method in class org.deeplearning4j.nn.modelimport.keras.layers.noise.KerasGaussianDropout
-
Get DL4J DropoutLayer with Gaussian dropout.
- getGaussianNoiseLayer() - Method in class org.deeplearning4j.nn.modelimport.keras.layers.noise.KerasGaussianNoise
-
Get DL4J DropoutLayer with Gaussian dropout.
- getGcName(MutableDirectBuffer, int, int) - Method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder.GcStatsDecoder
-
- getGcName(byte[], int, int) - Method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder.GcStatsDecoder
-
- getGen() - Method in class org.deeplearning4j.spark.models.embeddings.glove.GloveParam
-
- getGlobalPoolingLayer() - Method in class org.deeplearning4j.nn.modelimport.keras.layers.pooling.KerasGlobalPooling
-
Get DL4J SubsamplingLayer.
- getGradient(int, double) - Method in class org.deeplearning4j.models.embeddings.inmemory.InMemoryLookupTable
-
- getGradient(int, double) - Method in interface org.deeplearning4j.models.embeddings.WeightLookupTable
-
Returns gradient for specified word
- getGradient(int, double, double) - Method in class org.deeplearning4j.models.sequencevectors.sequence.SequenceElement
-
Deprecated.
- getGradientCheck() - Method in class org.deeplearning4j.nn.conf.layers.CenterLossOutputLayer
-
- getGradientFor(String) - Method in class org.deeplearning4j.nn.gradient.DefaultGradient
-
- getGradientFor(String) - Method in interface org.deeplearning4j.nn.gradient.Gradient
-
The gradient for the given variable
- getGradients() - Method in class org.deeplearning4j.ui.weights.beans.CompactModelAndGradient
-
- getGradientsAccumulator() - Method in interface org.deeplearning4j.optimize.api.ConvexOptimizer
-
This method returns GradientsAccumulator instance used in this optimizer.
- getGradientsAccumulator() - Method in class org.deeplearning4j.optimize.solvers.BaseOptimizer
-
- getGradientsFromFlattened(NeuralNetConfiguration, INDArray) - Method in interface org.deeplearning4j.nn.api.ParamInitializer
-
Return a map of gradients (in their standard non-flattened representation), taken from the flattened (row vector) gradientView array.
- getGradientsFromFlattened(NeuralNetConfiguration, INDArray) - Method in class org.deeplearning4j.nn.layers.ocnn.OCNNParamInitializer
-
- getGradientsFromFlattened(NeuralNetConfiguration, INDArray) - Method in class org.deeplearning4j.nn.params.BatchNormalizationParamInitializer
-
- getGradientsFromFlattened(NeuralNetConfiguration, INDArray) - Method in class org.deeplearning4j.nn.params.BidirectionalParamInitializer
-
- getGradientsFromFlattened(NeuralNetConfiguration, INDArray) - Method in class org.deeplearning4j.nn.params.CenterLossParamInitializer
-
- getGradientsFromFlattened(NeuralNetConfiguration, INDArray) - Method in class org.deeplearning4j.nn.params.Convolution3DParamInitializer
-
- getGradientsFromFlattened(NeuralNetConfiguration, INDArray) - Method in class org.deeplearning4j.nn.params.ConvolutionParamInitializer
-
- getGradientsFromFlattened(NeuralNetConfiguration, INDArray) - Method in class org.deeplearning4j.nn.params.DeconvolutionParamInitializer
-
- getGradientsFromFlattened(NeuralNetConfiguration, INDArray) - Method in class org.deeplearning4j.nn.params.DefaultParamInitializer
-
- getGradientsFromFlattened(NeuralNetConfiguration, INDArray) - Method in class org.deeplearning4j.nn.params.DepthwiseConvolutionParamInitializer
-
- getGradientsFromFlattened(NeuralNetConfiguration, INDArray) - Method in class org.deeplearning4j.nn.params.ElementWiseParamInitializer
-
Return a map of gradients (in their standard non-flattened representation), taken from the flattened (row vector) gradientView array.
- getGradientsFromFlattened(NeuralNetConfiguration, INDArray) - Method in class org.deeplearning4j.nn.params.EmptyParamInitializer
-
- getGradientsFromFlattened(NeuralNetConfiguration, INDArray) - Method in class org.deeplearning4j.nn.params.FrozenLayerParamInitializer
-
- getGradientsFromFlattened(NeuralNetConfiguration, INDArray) - Method in class org.deeplearning4j.nn.params.FrozenLayerWithBackpropParamInitializer
-
- getGradientsFromFlattened(NeuralNetConfiguration, INDArray) - Method in class org.deeplearning4j.nn.params.GravesBidirectionalLSTMParamInitializer
-
- getGradientsFromFlattened(NeuralNetConfiguration, INDArray) - Method in class org.deeplearning4j.nn.params.GravesLSTMParamInitializer
-
- getGradientsFromFlattened(NeuralNetConfiguration, INDArray) - Method in class org.deeplearning4j.nn.params.LSTMParamInitializer
-
- getGradientsFromFlattened(NeuralNetConfiguration, INDArray) - Method in class org.deeplearning4j.nn.params.PretrainParamInitializer
-
- getGradientsFromFlattened(NeuralNetConfiguration, INDArray) - Method in class org.deeplearning4j.nn.params.SameDiffParamInitializer
-
- getGradientsFromFlattened(NeuralNetConfiguration, INDArray) - Method in class org.deeplearning4j.nn.params.SeparableConvolutionParamInitializer
-
- getGradientsFromFlattened(NeuralNetConfiguration, INDArray) - Method in class org.deeplearning4j.nn.params.SimpleRnnParamInitializer
-
- getGradientsFromFlattened(NeuralNetConfiguration, INDArray) - Method in class org.deeplearning4j.nn.params.VariationalAutoencoderParamInitializer
-
- getGradientsFromFlattened(NeuralNetConfiguration, INDArray) - Method in class org.deeplearning4j.nn.params.WrapperLayerParamInitializer
-
- getGradientsViewArray() - Method in interface org.deeplearning4j.nn.api.Model
-
- getGradientsViewArray() - Method in class org.deeplearning4j.nn.graph.ComputationGraph
-
- getGradientsViewArray() - Method in class org.deeplearning4j.nn.layers.AbstractLayer
-
- getGradientsViewArray() - Method in class org.deeplearning4j.nn.layers.BaseLayer
-
- getGradientsViewArray() - Method in class org.deeplearning4j.nn.layers.recurrent.BidirectionalLayer
-
- getGradientsViewArray() - Method in class org.deeplearning4j.nn.layers.samediff.SameDiffLayer
-
- getGradientsViewArray() - Method in class org.deeplearning4j.nn.layers.variational.VariationalAutoencoder
-
- getGradientsViewArray() - Method in class org.deeplearning4j.nn.layers.wrapper.BaseWrapperLayer
-
- getGradientsViewArray() - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
-
- getGradientsViewArray() - Method in class org.deeplearning4j.plot.BarnesHutTsne
-
- getGradientUpdater() - Method in class org.deeplearning4j.nn.updater.UpdaterBlock
-
- getGraph() - Method in class org.deeplearning4j.graph.models.embeddings.GraphVectorsImpl
-
- getGraph() - Method in interface org.deeplearning4j.graph.models.GraphVectors
-
- getGraphWalkIterators(int) - Method in interface org.deeplearning4j.graph.iterator.parallel.GraphWalkIteratorProvider
-
Get a list of GraphWalkIterators.
- getGraphWalkIterators(int) - Method in class org.deeplearning4j.graph.iterator.parallel.RandomWalkGraphIteratorProvider
-
- getGraphWalkIterators(int) - Method in class org.deeplearning4j.graph.iterator.parallel.WeightedRandomWalkGraphIteratorProvider
-
- getGridHeight(int[]) - Static method in class org.deeplearning4j.zoo.model.helper.DarknetHelper
-
Returns inputShape[2] / 32, where inputShape[2] should be a multiple of 32.
- getGridWidth(int[]) - Static method in class org.deeplearning4j.zoo.model.helper.DarknetHelper
-
Returns inputShape[1] / 32, where inputShape[1] should be a multiple of 32.
- getGroups(String...) - Method in class org.deeplearning4j.nn.modelimport.keras.Hdf5Archive
-
Get list of groups from group path.
- getHardwareUID() - Static method in class org.deeplearning4j.util.UIDProvider
-
- getHasBiasFromConfig(Map<String, Object>, KerasLayerConfiguration) - Static method in class org.deeplearning4j.nn.modelimport.keras.utils.KerasLayerUtils
-
Determine if layer should be instantiated with bias
- getHashLength() - Method in interface org.deeplearning4j.clustering.lsh.LSH
-
Returns the size of a hash compared against in one hashing bucket, corresponding to an AND construction
denoting hashLength by h,
amplifies a (d1, d2, p1, p2) hash family into a
(d1, d2, p1^h, p2^h)-sensitive one (match probability is decreasing with h)
- getHeaderSize() - Method in class org.deeplearning4j.datasets.mnist.MnistDbFile
-
- getHeaderSize() - Method in class org.deeplearning4j.datasets.mnist.MnistImageFile
-
- getHeadWord() - Method in class org.deeplearning4j.nn.layers.feedforward.autoencoder.recursive.Tree
-
- getHeightAndWidth(NeuralNetConfiguration) - Static method in class org.deeplearning4j.util.ConvolutionUtils
-
Get the height and width
from the configuration
- getHeightAndWidth(int[]) - Static method in class org.deeplearning4j.util.ConvolutionUtils
-
Get the height and width
for an image
- getHh() - Method in class org.deeplearning4j.clustering.quadtree.Cell
-
- getHistograms(StatsType) - Method in interface org.deeplearning4j.ui.stats.api.StatsReport
-
Get the histograms for all parameters, for a given StatsType (Parameters/Updates/Activations)
- getHistograms(StatsType) - Method in class org.deeplearning4j.ui.stats.impl.java.JavaStatsReport
-
- getHistograms(StatsType) - Method in class org.deeplearning4j.ui.stats.impl.SbeStatsReport
-
- getHistoricalGradient() - Method in class org.deeplearning4j.models.sequencevectors.sequence.SequenceElement
-
Deprecated.
- getHosts() - Method in class org.deeplearning4j.aws.ec2.Ec2BoxCreator
-
- getHw() - Method in class org.deeplearning4j.clustering.quadtree.Cell
-
- getHwDeviceDescription() - Method in interface org.deeplearning4j.ui.stats.api.StatsInitializationReport
-
- getHwDeviceTotalMemory() - Method in interface org.deeplearning4j.ui.stats.api.StatsInitializationReport
-
- getHWDFromInputType(InputType) - Static method in class org.deeplearning4j.util.ConvolutionUtils
-
Get heigh/width/channels as length 3 int[] from the InputType
- getHwHardwareUID() - Method in interface org.deeplearning4j.ui.stats.api.StatsInitializationReport
-
- getHwHardwareUID(MutableDirectBuffer, int, int) - Method in class org.deeplearning4j.ui.stats.sbe.StaticInfoDecoder
-
- getHwHardwareUID(byte[], int, int) - Method in class org.deeplearning4j.ui.stats.sbe.StaticInfoDecoder
-
- getHwJvmAvailableProcessors() - Method in interface org.deeplearning4j.ui.stats.api.StatsInitializationReport
-
- getHwJvmMaxMemory() - Method in interface org.deeplearning4j.ui.stats.api.StatsInitializationReport
-
- getHwNumDevices() - Method in interface org.deeplearning4j.ui.stats.api.StatsInitializationReport
-
- getHwOffHeapMaxMemory() - Method in interface org.deeplearning4j.ui.stats.api.StatsInitializationReport
-
- getHyperPlaneAt(int) - Method in class org.deeplearning4j.clustering.randomprojection.RPHyperPlanes
-
- getId(String) - Static method in class org.ansj.library.DATDictionary
-
- getImages() - Method in class org.deeplearning4j.datasets.mnist.MnistManager
-
- getInboundLayerNames() - Method in class org.deeplearning4j.nn.modelimport.keras.KerasLayer
-
Get list of inbound layers.
- getInboundLayerNamesFromConfig(Map<String, Object>, KerasLayerConfiguration) - Static method in class org.deeplearning4j.nn.modelimport.keras.utils.KerasLayerUtils
-
Get list of inbound layers from Keras layer configuration.
- getINDArray() - Method in class org.deeplearning4j.streaming.kafka.NDArrayConsumer
-
- getIndex() - Method in interface org.deeplearning4j.bagofwords.vectorizer.TextVectorizer
-
Inverted index
- getIndex() - Method in class org.deeplearning4j.clustering.sptree.HeapItem
-
- getIndex() - Method in class org.deeplearning4j.clustering.sptree.SpTree
-
- getIndex() - Method in class org.deeplearning4j.models.sequencevectors.sequence.SequenceElement
-
Returns index in Huffman tree
- getIndex() - Method in interface org.deeplearning4j.nn.api.Layer
-
Get the layer index.
- getIndex() - Method in class org.deeplearning4j.nn.layers.AbstractLayer
-
- getIndex() - Method in class org.deeplearning4j.nn.layers.normalization.BatchNormalization
-
- getIndex() - Method in class org.deeplearning4j.nn.layers.recurrent.BidirectionalLayer
-
- getIndex() - Method in class org.deeplearning4j.nn.layers.variational.VariationalAutoencoder
-
- getIndex() - Method in class org.deeplearning4j.nn.layers.wrapper.BaseWrapperLayer
-
- getIndex() - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
-
- getInDimension() - Method in interface org.deeplearning4j.clustering.lsh.LSH
-
- getInitConfig() - Method in class org.deeplearning4j.ui.stats.BaseStatsListener
-
- getInitialClusterCount() - Method in class org.deeplearning4j.clustering.strategy.BaseClusteringStrategy
-
- getInitialClusterCount() - Method in interface org.deeplearning4j.clustering.strategy.ClusteringStrategy
-
- getInitialModel() - Method in interface org.deeplearning4j.spark.api.TrainingWorker
-
Get the initial model when training a MultiLayerNetwork/SparkDl4jMultiLayer
- getInitialModel() - Method in class org.deeplearning4j.spark.impl.paramavg.ParameterAveragingTrainingWorker
-
- getInitialModel() - Method in class org.deeplearning4j.spark.parameterserver.training.SharedTrainingWorker
-
- getInitialModelGraph() - Method in interface org.deeplearning4j.spark.api.TrainingWorker
-
Get the initial model when training a ComputationGraph/SparkComputationGraph
- getInitialModelGraph() - Method in class org.deeplearning4j.spark.impl.paramavg.ParameterAveragingTrainingWorker
-
- getInitialModelGraph() - Method in class org.deeplearning4j.spark.parameterserver.training.SharedTrainingWorker
-
- getInitTypeClass() - Method in interface org.deeplearning4j.api.storage.StorageMetaData
-
Full class name for the initialization information that will be posted.
- getInitTypeClass(MutableDirectBuffer, int, int) - Method in class org.deeplearning4j.ui.stats.sbe.StorageMetaDataDecoder
-
- getInitTypeClass(byte[], int, int) - Method in class org.deeplearning4j.ui.stats.sbe.StorageMetaDataDecoder
-
- getInnerConf(NeuralNetConfiguration) - Method in class org.deeplearning4j.nn.conf.layers.misc.FrozenLayer
-
- getInnerConf(NeuralNetConfiguration) - Method in class org.deeplearning4j.nn.conf.layers.misc.FrozenLayerWithBackprop
-
- getInnerLayerConfigFromConfig(Map<String, Object>, KerasLayerConfiguration) - Static method in class org.deeplearning4j.nn.modelimport.keras.utils.KerasLayerUtils
-
Get inner layer config from Keras layer configuration.
- getInnerNodeVector(int) - Method in class org.deeplearning4j.graph.models.embeddings.InMemoryGraphLookupTable
-
- getInput(int) - Method in class org.deeplearning4j.nn.graph.ComputationGraph
-
Get the previously set input for the ComputationGraph
- getInput() - Method in class org.deeplearning4j.nn.layers.AbstractLayer
-
- getInput() - Method in class org.deeplearning4j.nn.layers.recurrent.RnnOutputLayer
-
- getInput() - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
-
- getInputBatches() - Method in interface org.deeplearning4j.parallelism.inference.InferenceObservable
-
Get input batches - and their associated input mask arrays, if any
Note that usually the returned list will be of size 1 - however, in the batched case, not all inputs
can actually be batched (variable size inputs to fully convolutional net, for example).
- getInputBatches() - Method in class org.deeplearning4j.parallelism.inference.observers.BasicInferenceObservable
-
- getInputBatches() - Method in class org.deeplearning4j.parallelism.inference.observers.BatchedInferenceObservable
-
- getInputMaskArrays() - Method in class org.deeplearning4j.nn.graph.ComputationGraph
-
Get the previously set feature/input mask arrays for the ComputationGraph
- getInputMiniBatchSize() - Method in interface org.deeplearning4j.nn.api.Layer
-
Get current/last input mini-batch size, as set by setInputMiniBatchSize(int)
- getInputMiniBatchSize() - Method in class org.deeplearning4j.nn.layers.AbstractLayer
-
- getInputMiniBatchSize() - Method in class org.deeplearning4j.nn.layers.recurrent.BidirectionalLayer
-
- getInputMiniBatchSize() - Method in class org.deeplearning4j.nn.layers.variational.VariationalAutoencoder
-
- getInputMiniBatchSize() - Method in class org.deeplearning4j.nn.layers.wrapper.BaseWrapperLayer
-
- getInputMiniBatchSize() - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
-
- getInputPreProcess(int) - Method in class org.deeplearning4j.nn.conf.MultiLayerConfiguration
-
- getInputPreprocessor(InputType...) - Method in class org.deeplearning4j.nn.modelimport.keras.KerasLayer
-
Gets appropriate DL4J InputPreProcessor for given InputTypes.
- getInputPreprocessor(InputType...) - Method in class org.deeplearning4j.nn.modelimport.keras.layers.convolutional.KerasConvolution1D
-
Gets appropriate DL4J InputPreProcessor for given InputTypes.
- getInputPreprocessor(InputType...) - Method in class org.deeplearning4j.nn.modelimport.keras.layers.core.KerasFlatten
-
Gets appropriate DL4J InputPreProcessor for given InputTypes.
- getInputPreprocessor(InputType...) - Method in class org.deeplearning4j.nn.modelimport.keras.layers.core.KerasPermute
-
Gets appropriate DL4J InputPreProcessor for given InputTypes.
- getInputPreprocessor(InputType...) - Method in class org.deeplearning4j.nn.modelimport.keras.layers.core.KerasReshape
-
Gets appropriate DL4J InputPreProcessor for given InputTypes.
- getInputPreprocessor(InputType...) - Method in class org.deeplearning4j.nn.modelimport.keras.layers.pooling.KerasGlobalPooling
-
Gets appropriate DL4J InputPreProcessor for given InputTypes.
- getInputPreprocessor(InputType...) - Method in class org.deeplearning4j.nn.modelimport.keras.layers.recurrent.KerasLstm
-
Gets appropriate DL4J InputPreProcessor for given InputTypes.
- getInputPreprocessor(InputType...) - Method in class org.deeplearning4j.nn.modelimport.keras.layers.recurrent.KerasSimpleRnn
-
Gets appropriate DL4J InputPreProcessor for given InputTypes.
- getInputPreprocessor(InputType...) - Method in class org.deeplearning4j.nn.modelimport.keras.layers.wrappers.KerasBidirectional
-
Gets appropriate DL4J InputPreProcessor for given InputTypes.
- getInputs() - Method in class org.deeplearning4j.nn.graph.ComputationGraph
-
Get the previously set inputs for the ComputationGraph
- getInputs() - Method in class org.deeplearning4j.nn.graph.vertex.BaseWrapperVertex
-
- getInputs() - Method in interface org.deeplearning4j.nn.graph.vertex.GraphVertex
-
Get the array of inputs previously set for this GraphVertex
- getInputShape() - Method in class org.deeplearning4j.nn.modelimport.keras.KerasLayer
-
Get layer input shape.
- getInputShapeFromConfig(Map<String, Object>, KerasLayerConfiguration) - Static method in class org.deeplearning4j.nn.modelimport.keras.utils.KerasLayerUtils
-
Get Keras input shape from Keras layer configuration.
- getInputStream(String) - Static method in class org.ansj.dic.DicReader
-
- getInputStream() - Method in class org.deeplearning4j.ui.i18n.I18NResource
-
- getInputVertices() - Method in class org.deeplearning4j.nn.graph.vertex.BaseGraphVertex
-
A representation of the vertices that are inputs to this vertex (inputs duing forward pass)
Specifically, if inputVertices[X].getVertexIndex() = Y, and inputVertices[X].getVertexEdgeNumber() = Z
then the Zth output of vertex Y is the Xth input to this vertex
- getInputVertices() - Method in class org.deeplearning4j.nn.graph.vertex.BaseWrapperVertex
-
- getInputVertices() - Method in interface org.deeplearning4j.nn.graph.vertex.GraphVertex
-
A representation of the vertices that are inputs to this vertex (inputs duing forward pass)
Specifically, if inputVertices[X].getVertexIndex() = Y, and inputVertices[X].getVertexEdgeNumber() = Z
then the Zth output connection (see
GraphVertex.getNumOutputConnections() of vertex Y is the Xth input to this vertex
- getInsideLayer() - Method in class org.deeplearning4j.nn.layers.FrozenLayer
-
- getInsideLayer() - Method in class org.deeplearning4j.nn.layers.FrozenLayerWithBackprop
-
- getInstance() - Static method in class org.deeplearning4j.nn.layers.ocnn.OCNNParamInitializer
-
- getInstance() - Static method in class org.deeplearning4j.nn.params.BatchNormalizationParamInitializer
-
- getInstance() - Static method in class org.deeplearning4j.nn.params.CenterLossParamInitializer
-
- getInstance() - Static method in class org.deeplearning4j.nn.params.Convolution3DParamInitializer
-
- getInstance() - Static method in class org.deeplearning4j.nn.params.ConvolutionParamInitializer
-
- getInstance() - Static method in class org.deeplearning4j.nn.params.DeconvolutionParamInitializer
-
- getInstance() - Static method in class org.deeplearning4j.nn.params.DefaultParamInitializer
-
- getInstance() - Static method in class org.deeplearning4j.nn.params.DepthwiseConvolutionParamInitializer
-
- getInstance() - Static method in class org.deeplearning4j.nn.params.ElementWiseParamInitializer
-
- getInstance() - Static method in class org.deeplearning4j.nn.params.EmptyParamInitializer
-
- getInstance() - Static method in class org.deeplearning4j.nn.params.FrozenLayerParamInitializer
-
- getInstance() - Static method in class org.deeplearning4j.nn.params.FrozenLayerWithBackpropParamInitializer
-
- getInstance() - Static method in class org.deeplearning4j.nn.params.GravesBidirectionalLSTMParamInitializer
-
- getInstance() - Static method in class org.deeplearning4j.nn.params.GravesLSTMParamInitializer
-
- getInstance() - Static method in class org.deeplearning4j.nn.params.LSTMParamInitializer
-
- getInstance() - Static method in class org.deeplearning4j.nn.params.PretrainParamInitializer
-
- getInstance() - Static method in class org.deeplearning4j.nn.params.SameDiffParamInitializer
-
- getInstance() - Static method in class org.deeplearning4j.nn.params.SeparableConvolutionParamInitializer
-
- getInstance() - Static method in class org.deeplearning4j.nn.params.SimpleRnnParamInitializer
-
- getInstance() - Static method in class org.deeplearning4j.nn.params.VariationalAutoencoderParamInitializer
-
- getInstance() - Static method in class org.deeplearning4j.nn.params.WrapperLayerParamInitializer
-
- getInstance() - Static method in class org.deeplearning4j.spark.models.embeddings.word2vec.NegativeHolder
-
- getInstance() - Static method in class org.deeplearning4j.spark.models.embeddings.word2vec.VocabHolder
-
- getInstance() - Static method in class org.deeplearning4j.spark.parameterserver.pw.SharedTrainingWrapper
-
- getInstance() - Static method in class org.deeplearning4j.spark.time.NTPTimeSource
-
- getInstance() - Static method in class org.deeplearning4j.spark.time.SystemClockTimeSource
-
- getInstance() - Static method in class org.deeplearning4j.spark.time.TimeSourceProvider
-
Get a TimeSource
the default TimeSource instance (default:
NTPTimeSource
- getInstance(String) - Static method in class org.deeplearning4j.spark.time.TimeSourceProvider
-
Get a specific TimeSource by class name
- getInstance() - Static method in class org.deeplearning4j.ui.api.UIServer
-
Get (and, initialize if necessary) the UI server.
- getInstance() - Static method in class org.deeplearning4j.ui.i18n.DefaultI18N
-
- getInstance() - Static method in class org.deeplearning4j.ui.i18n.I18NProvider
-
Get the current/global I18N instance
- getInstance() - Static method in class org.deeplearning4j.ui.WebReporter
-
- getInternationalizationResources() - Method in interface org.deeplearning4j.ui.api.UIModule
-
- getInternationalizationResources() - Method in class org.deeplearning4j.ui.module.convolutional.ConvolutionalListenerModule
-
- getInternationalizationResources() - Method in class org.deeplearning4j.ui.module.defaultModule.DefaultModule
-
- getInternationalizationResources() - Method in class org.deeplearning4j.ui.module.remote.RemoteReceiverModule
-
- getInternationalizationResources() - Method in class org.deeplearning4j.ui.module.train.TrainModule
-
- getInternationalizationResources() - Method in class org.deeplearning4j.ui.module.tsne.TsneModule
-
- getIs() - Method in class org.deeplearning4j.models.word2vec.StreamWork
-
- getIsCollectTrainingStats() - Method in interface org.deeplearning4j.spark.api.TrainingMaster
-
Get the current setting for collectTrainingStats
- getIsCollectTrainingStats() - Method in class org.deeplearning4j.spark.impl.paramavg.ParameterAveragingTrainingMaster
-
- getIsCollectTrainingStats() - Method in class org.deeplearning4j.spark.parameterserver.training.SharedTrainingMaster
-
- getItem(int) - Static method in class org.ansj.library.DATDictionary
-
- getItem(String) - Static method in class org.ansj.library.DATDictionary
-
- getItem() - Method in class org.ansj.splitWord.impl.GetWordsImpl
-
- getIter(Model) - Static method in class org.deeplearning4j.optimize.listeners.checkpoint.CheckpointListener
-
- getIterationCount() - Method in class org.deeplearning4j.clustering.iteration.IterationHistory
-
- getIterationCount() - Method in interface org.deeplearning4j.nn.api.Layer
-
- getIterationCount() - Method in class org.deeplearning4j.nn.layers.recurrent.BidirectionalLayer
-
- getIterationCount() - Method in class org.deeplearning4j.nn.layers.wrapper.BaseWrapperLayer
-
- getIterationCount() - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
-
- getIterationCount(Model) - Static method in class org.deeplearning4j.optimize.solvers.BaseOptimizer
-
- getIterationCount() - Method in interface org.deeplearning4j.ui.stats.api.StatsReport
-
Get the current iteration number
- getIterationInfo(int) - Method in class org.deeplearning4j.clustering.iteration.IterationHistory
-
- getIterations() - Method in class org.deeplearning4j.spark.models.embeddings.word2vec.Word2VecPerformerVoid
-
Deprecated.
- getIUpdaterWithDefaultConfig() - Method in enum org.deeplearning4j.nn.conf.Updater
-
- getJsonMapper() - Static method in class org.deeplearning4j.spark.impl.paramavg.BaseTrainingMaster
-
- getJvmCurrentBytes() - Method in interface org.deeplearning4j.ui.stats.api.StatsReport
-
Get JVM memory - current bytes used
- getJvmID() - Method in class org.deeplearning4j.spark.stats.BaseEventStats
-
- getJvmID() - Method in interface org.deeplearning4j.spark.stats.EventStats
-
- getJvmMaxBytes() - Method in interface org.deeplearning4j.ui.stats.api.StatsReport
-
Get JVM memory - max available bytes
- getJVMUID() - Static method in class org.deeplearning4j.util.UIDProvider
-
- getK() - Method in class org.ansj.domain.KV
-
- getKerasLayerFromConfig(Map<String, Object>, KerasLayerConfiguration, Map<String, Class<? extends KerasLayer>>, Map<String, ? extends KerasLayer>) - Static method in class org.deeplearning4j.nn.modelimport.keras.utils.KerasLayerUtils
-
Build KerasLayer from a Keras layer configuration.
- getKerasLayerFromConfig(Map<String, Object>, boolean, KerasLayerConfiguration, Map<String, Class<? extends KerasLayer>>, Map<String, ? extends KerasLayer>) - Static method in class org.deeplearning4j.nn.modelimport.keras.utils.KerasLayerUtils
-
Build KerasLayer from a Keras layer configuration.
- getKerasMajorVersion() - Method in class org.deeplearning4j.nn.modelimport.keras.KerasLayer
-
Get Keras major version of this layer.
- getKernelSizeFromConfig(Map<String, Object>, int, KerasLayerConfiguration, int) - Static method in class org.deeplearning4j.nn.modelimport.keras.layers.convolutional.KerasConvolutionUtils
-
Get (convolution) kernel size from Keras layer configuration.
- getKey() - Method in class com.atilika.kuromoji.trie.PatriciaTrie.PatriciaNode
-
Get this node's key
- getKey() - Method in class com.atilika.kuromoji.trie.Trie.Node
-
Return this node's key
- getKeyMapper() - Method in class com.atilika.kuromoji.trie.PatriciaTrie
-
- getKeySet() - Method in class org.deeplearning4j.spark.api.stats.CommonSparkTrainingStats
-
- getKeySet() - Method in interface org.deeplearning4j.spark.api.stats.SparkTrainingStats
-
- getKeySet() - Method in class org.deeplearning4j.spark.impl.paramavg.stats.ParameterAveragingTrainingMasterStats
-
- getKeySet() - Method in class org.deeplearning4j.spark.impl.paramavg.stats.ParameterAveragingTrainingWorkerStats
-
- getKeyWords() - Method in class org.ansj.app.summary.pojo.Summary
-
- getL1ByParam(String) - Method in class org.deeplearning4j.nn.conf.layers.AbstractLSTM
-
- getL1ByParam(String) - Method in class org.deeplearning4j.nn.conf.layers.ActivationLayer
-
- getL1ByParam(String) - Method in class org.deeplearning4j.nn.conf.layers.BasePretrainNetwork
-
- getL1ByParam(String) - Method in class org.deeplearning4j.nn.conf.layers.BaseUpsamplingLayer
-
- getL1ByParam(String) - Method in class org.deeplearning4j.nn.conf.layers.BatchNormalization
-
- getL1ByParam(String) - Method in class org.deeplearning4j.nn.conf.layers.CenterLossOutputLayer
-
- getL1ByParam(String) - Method in class org.deeplearning4j.nn.conf.layers.ConvolutionLayer
-
- getL1ByParam(String) - Method in class org.deeplearning4j.nn.conf.layers.DropoutLayer
-
- getL1ByParam(String) - Method in class org.deeplearning4j.nn.conf.layers.FeedForwardLayer
-
- getL1ByParam(String) - Method in class org.deeplearning4j.nn.conf.layers.GlobalPoolingLayer
-
- getL1ByParam(String) - Method in class org.deeplearning4j.nn.conf.layers.GravesBidirectionalLSTM
-
Deprecated.
- getL1ByParam(String) - Method in class org.deeplearning4j.nn.conf.layers.Layer
-
Get the L1 coefficient for the given parameter.
- getL1ByParam(String) - Method in class org.deeplearning4j.nn.conf.layers.LocalResponseNormalization
-
- getL1ByParam(String) - Method in class org.deeplearning4j.nn.conf.layers.misc.FrozenLayer
-
- getL1ByParam(String) - Method in class org.deeplearning4j.nn.conf.layers.misc.FrozenLayerWithBackprop
-
- getL1ByParam(String) - Method in class org.deeplearning4j.nn.conf.layers.NoParamLayer
-
- getL1ByParam(String) - Method in class org.deeplearning4j.nn.conf.layers.objdetect.Yolo2OutputLayer
-
- getL1ByParam(String) - Method in class org.deeplearning4j.nn.conf.layers.recurrent.Bidirectional
-
- getL1ByParam(String) - Method in class org.deeplearning4j.nn.conf.layers.recurrent.SimpleRnn
-
- getL1ByParam(String) - Method in class org.deeplearning4j.nn.conf.layers.samediff.AbstractSameDiffLayer
-
- getL1ByParam(String) - Method in class org.deeplearning4j.nn.conf.layers.SeparableConvolution2D
-
- getL1ByParam(String) - Method in class org.deeplearning4j.nn.conf.layers.SpaceToBatchLayer
-
- getL1ByParam(String) - Method in class org.deeplearning4j.nn.conf.layers.SpaceToDepthLayer
-
- getL1ByParam(String) - Method in class org.deeplearning4j.nn.conf.layers.Subsampling3DLayer
-
- getL1ByParam(String) - Method in class org.deeplearning4j.nn.conf.layers.SubsamplingLayer
-
- getL1ByParam(String) - Method in class org.deeplearning4j.nn.conf.layers.util.MaskLayer
-
- getL1ByParam(String) - Method in class org.deeplearning4j.nn.conf.layers.util.MaskZeroLayer
-
- getL1ByParam(String) - Method in class org.deeplearning4j.nn.conf.layers.variational.VariationalAutoencoder
-
- getL1ByParam(String) - Method in class org.deeplearning4j.nn.conf.layers.wrapper.BaseWrapperLayer
-
- getL1ByParam(String) - Method in class org.deeplearning4j.nn.conf.layers.ZeroPadding1DLayer
-
- getL1ByParam(String) - Method in class org.deeplearning4j.nn.conf.layers.ZeroPadding3DLayer
-
- getL1ByParam(String) - Method in class org.deeplearning4j.nn.conf.NeuralNetConfiguration
-
- getL1ByParam(String) - Method in class org.deeplearning4j.nn.conf.ocnn.OCNNOutputLayer
-
- getL2ByParam(String) - Method in class org.deeplearning4j.nn.conf.layers.AbstractLSTM
-
- getL2ByParam(String) - Method in class org.deeplearning4j.nn.conf.layers.ActivationLayer
-
- getL2ByParam(String) - Method in class org.deeplearning4j.nn.conf.layers.BasePretrainNetwork
-
- getL2ByParam(String) - Method in class org.deeplearning4j.nn.conf.layers.BaseUpsamplingLayer
-
- getL2ByParam(String) - Method in class org.deeplearning4j.nn.conf.layers.BatchNormalization
-
- getL2ByParam(String) - Method in class org.deeplearning4j.nn.conf.layers.CenterLossOutputLayer
-
- getL2ByParam(String) - Method in class org.deeplearning4j.nn.conf.layers.ConvolutionLayer
-
- getL2ByParam(String) - Method in class org.deeplearning4j.nn.conf.layers.DropoutLayer
-
- getL2ByParam(String) - Method in class org.deeplearning4j.nn.conf.layers.FeedForwardLayer
-
- getL2ByParam(String) - Method in class org.deeplearning4j.nn.conf.layers.GlobalPoolingLayer
-
- getL2ByParam(String) - Method in class org.deeplearning4j.nn.conf.layers.GravesBidirectionalLSTM
-
Deprecated.
- getL2ByParam(String) - Method in class org.deeplearning4j.nn.conf.layers.Layer
-
Get the L2 coefficient for the given parameter.
- getL2ByParam(String) - Method in class org.deeplearning4j.nn.conf.layers.LocalResponseNormalization
-
- getL2ByParam(String) - Method in class org.deeplearning4j.nn.conf.layers.misc.FrozenLayer
-
- getL2ByParam(String) - Method in class org.deeplearning4j.nn.conf.layers.misc.FrozenLayerWithBackprop
-
- getL2ByParam(String) - Method in class org.deeplearning4j.nn.conf.layers.NoParamLayer
-
- getL2ByParam(String) - Method in class org.deeplearning4j.nn.conf.layers.objdetect.Yolo2OutputLayer
-
- getL2ByParam(String) - Method in class org.deeplearning4j.nn.conf.layers.recurrent.Bidirectional
-
- getL2ByParam(String) - Method in class org.deeplearning4j.nn.conf.layers.recurrent.SimpleRnn
-
- getL2ByParam(String) - Method in class org.deeplearning4j.nn.conf.layers.samediff.AbstractSameDiffLayer
-
- getL2ByParam(String) - Method in class org.deeplearning4j.nn.conf.layers.SeparableConvolution2D
-
- getL2ByParam(String) - Method in class org.deeplearning4j.nn.conf.layers.SpaceToBatchLayer
-
- getL2ByParam(String) - Method in class org.deeplearning4j.nn.conf.layers.SpaceToDepthLayer
-
- getL2ByParam(String) - Method in class org.deeplearning4j.nn.conf.layers.Subsampling3DLayer
-
- getL2ByParam(String) - Method in class org.deeplearning4j.nn.conf.layers.SubsamplingLayer
-
- getL2ByParam(String) - Method in class org.deeplearning4j.nn.conf.layers.util.MaskLayer
-
- getL2ByParam(String) - Method in class org.deeplearning4j.nn.conf.layers.util.MaskZeroLayer
-
- getL2ByParam(String) - Method in class org.deeplearning4j.nn.conf.layers.variational.VariationalAutoencoder
-
- getL2ByParam(String) - Method in class org.deeplearning4j.nn.conf.layers.wrapper.BaseWrapperLayer
-
- getL2ByParam(String) - Method in class org.deeplearning4j.nn.conf.layers.ZeroPadding1DLayer
-
- getL2ByParam(String) - Method in class org.deeplearning4j.nn.conf.layers.ZeroPadding3DLayer
-
- getL2ByParam(String) - Method in class org.deeplearning4j.nn.conf.NeuralNetConfiguration
-
- getL2ByParam(String) - Method in class org.deeplearning4j.nn.conf.ocnn.OCNNOutputLayer
-
- getLabel() - Method in class org.deeplearning4j.models.sequencevectors.sequence.SequenceElement
-
This method should return string representation of this SequenceElement, so it can be used for
- getLabel() - Method in class org.deeplearning4j.models.sequencevectors.sequence.ShallowSequenceElement
-
- getLabel() - Method in class org.deeplearning4j.models.word2vec.VocabWord
-
- getLabel() - Method in class org.deeplearning4j.models.word2vec.VocabWork
-
- getLabel() - Method in class org.deeplearning4j.text.documentiterator.LabelledDocument
-
Deprecated.
- getLabel(int) - Method in interface org.deeplearning4j.text.labels.LabelsProvider
-
- getLabel() - Method in class org.deeplearning4j.text.movingwindow.Window
-
- getLabel(int) - Method in class org.deeplearning4j.zoo.util.BaseLabels
-
- getLabel(int) - Method in class org.deeplearning4j.zoo.util.imagenet.ImageNetLabels
-
Returns the description of tne nth class in the 1000 classes of ImageNet.
- getLabel(int) - Method in interface org.deeplearning4j.zoo.util.Labels
-
Returns the description of the nth class from the classes of a dataset.
- getLabelClassMap() - Method in class org.deeplearning4j.iterator.CnnSentenceDataSetIterator
-
- getLabelCountsEachClass() - Method in class org.deeplearning4j.eval.EvaluationCalibration
-
- getLabelMaskArrays() - Method in class org.deeplearning4j.nn.graph.ComputationGraph
-
Get the previously set label/output mask arrays for the ComputationGraph
- getLabels() - Method in class org.deeplearning4j.datasets.datavec.RecordReaderDataSetIterator
-
- getLabels() - Method in class org.deeplearning4j.datasets.datavec.SequenceRecordReaderDataSetIterator
-
- getLabels() - Method in class org.deeplearning4j.datasets.iterator.AbstractDataSetIterator
-
Get dataset iterator record reader labels
- getLabels() - Method in class org.deeplearning4j.datasets.iterator.AsyncDataSetIterator
-
Get dataset iterator record reader labels
- getLabels() - Method in class org.deeplearning4j.datasets.iterator.AsyncShieldDataSetIterator
-
Get dataset iterator record reader labels
- getLabels() - Method in class org.deeplearning4j.datasets.iterator.BaseDatasetIterator
-
- getLabels() - Method in class org.deeplearning4j.datasets.iterator.EarlyTerminationDataSetIterator
-
- getLabels() - Method in class org.deeplearning4j.datasets.iterator.ExistingDataSetIterator
-
- getLabels() - Method in class org.deeplearning4j.datasets.iterator.FileSplitDataSetIterator
-
- getLabels() - Method in class org.deeplearning4j.datasets.iterator.impl.BenchmarkDataSetIterator
-
- getLabels() - Method in class org.deeplearning4j.datasets.iterator.impl.CifarDataSetIterator
-
- getLabels() - Method in class org.deeplearning4j.datasets.iterator.impl.EmnistDataSetIterator
-
Get the labels as a List
- getLabels(EmnistDataSetIterator.Set) - Static method in class org.deeplearning4j.datasets.iterator.impl.EmnistDataSetIterator
-
Get the label assignments for the given set as a List
- getLabels() - Method in class org.deeplearning4j.datasets.iterator.impl.ListDataSetIterator
-
- getLabels() - Method in class org.deeplearning4j.datasets.iterator.IteratorDataSetIterator
-
- getLabels() - Method in class org.deeplearning4j.datasets.iterator.MultiDataSetWrapperIterator
-
- getLabels() - Method in class org.deeplearning4j.datasets.iterator.MultipleEpochsIterator
-
Deprecated.
- getLabels() - Method in class org.deeplearning4j.datasets.iterator.parallel.BaseParallelDataSetIterator
-
- getLabels() - Method in class org.deeplearning4j.datasets.iterator.ReconstructionDataSetIterator
-
- getLabels() - Method in class org.deeplearning4j.datasets.iterator.SamplingDataSetIterator
-
- getLabels() - Method in class org.deeplearning4j.datasets.iterator.WorkspacesShieldDataSetIterator
-
- getLabels() - Method in class org.deeplearning4j.datasets.mnist.MnistManager
-
- getLabels() - Method in class org.deeplearning4j.datasets.test.TestDataSetIterator
-
- getLabels() - Method in class org.deeplearning4j.iterator.CnnSentenceDataSetIterator
-
- getLabels(List<BasicModelUtils.WordSimilarity>, int) - Static method in class org.deeplearning4j.models.embeddings.reader.impl.BasicModelUtils
-
- getLabels() - Method in class org.deeplearning4j.models.word2vec.iterator.Word2VecDataFetcher
-
- getLabels() - Method in class org.deeplearning4j.models.word2vec.iterator.Word2VecDataSetIterator
-
- getLabels() - Method in interface org.deeplearning4j.nn.api.layers.IOutputLayer
-
- getLabels() - Method in class org.deeplearning4j.nn.layers.BaseOutputLayer
-
- getLabels() - Method in class org.deeplearning4j.nn.layers.LossLayer
-
- getLabels() - Method in class org.deeplearning4j.nn.layers.ocnn.OCNNOutputLayer
-
- getLabels() - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
-
- getLabels() - Method in class org.deeplearning4j.spark.datavec.iterator.SparkSourceDummyReader
-
- getLabels() - Method in class org.deeplearning4j.spark.iterator.BaseDataSetIterator
-
- getLabels() - Method in class org.deeplearning4j.spark.parameterserver.iterators.VirtualDataSetIterator
-
- getLabels() - Method in class org.deeplearning4j.text.documentiterator.LabelsSource
-
This method returns the list of labels used by this generator instance.
- getLabels() - Method in class org.deeplearning4j.zoo.util.BaseLabels
-
- getLabels(String) - Method in class org.deeplearning4j.zoo.util.BaseLabels
-
Returns labels based on the text file resource.
- getLabels() - Method in class org.deeplearning4j.zoo.util.imagenet.ImageNetLabels
-
- getLabels2d(LayerWorkspaceMgr, ArrayType) - Method in class org.deeplearning4j.nn.layers.BaseOutputLayer
-
- getLabels2d() - Method in class org.deeplearning4j.nn.layers.LossLayer
-
- getLabels2d(LayerWorkspaceMgr, ArrayType) - Method in class org.deeplearning4j.nn.layers.ocnn.OCNNOutputLayer
-
- getLabels2d(LayerWorkspaceMgr, ArrayType) - Method in class org.deeplearning4j.nn.layers.OutputLayer
-
- getLabels2d(LayerWorkspaceMgr, ArrayType) - Method in class org.deeplearning4j.nn.layers.recurrent.RnnOutputLayer
-
- getLabels2d(LayerWorkspaceMgr, ArrayType) - Method in class org.deeplearning4j.nn.layers.training.CenterLossOutputLayer
-
- getLabelsArray(EmnistDataSetIterator.Set) - Static method in class org.deeplearning4j.datasets.iterator.impl.EmnistDataSetIterator
-
Get the label assignments for the given set as a character array.
- getLabelsArrays() - Method in class org.deeplearning4j.datasets.iterator.impl.EmnistDataSetIterator
-
Get the labels as a character array
- getLabelsSource() - Method in class org.deeplearning4j.bagofwords.vectorizer.BaseTextVectorizer
-
- getLabelsSource() - Method in class org.deeplearning4j.text.documentiterator.AsyncLabelAwareIterator
-
- getLabelsSource() - Method in class org.deeplearning4j.text.documentiterator.BasicLabelAwareIterator
-
This method returns LabelsSource instance, containing all labels derived from this iterator
- getLabelsSource() - Method in class org.deeplearning4j.text.documentiterator.FileLabelAwareIterator
-
- getLabelsSource() - Method in class org.deeplearning4j.text.documentiterator.FilenamesLabelAwareIterator
-
- getLabelsSource() - Method in class org.deeplearning4j.text.documentiterator.interoperability.DocumentIteratorConverter
-
- getLabelsSource() - Method in interface org.deeplearning4j.text.documentiterator.LabelAwareIterator
-
- getLabelsSource() - Method in class org.deeplearning4j.text.documentiterator.SimpleLabelAwareIterator
-
This method returns LabelsSource instance, containing all labels derived from this iterator
- getLabelsSource() - Method in class org.deeplearning4j.text.sentenceiterator.interoperability.SentenceIteratorConverter
-
- getLambda() - Method in class org.deeplearning4j.nn.conf.layers.CenterLossOutputLayer
-
- getLastChecked() - Method in class org.deeplearning4j.spark.models.embeddings.word2vec.Word2VecParam
-
Deprecated.
- getLastChecked() - Method in class org.deeplearning4j.spark.models.embeddings.word2vec.Word2VecPerformerVoid
-
Deprecated.
- getLastEtlTime() - Method in class org.deeplearning4j.nn.graph.ComputationGraph
-
This method returns ETL time field value
- getLastEtlTime() - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
-
- getLastUpdateTime() - Method in class org.deeplearning4j.ui.weights.beans.CompactModelAndGradient
-
- getLastWords() - Method in class org.deeplearning4j.spark.models.embeddings.word2vec.Word2VecParam
-
Deprecated.
- getLatestModel() - Method in interface org.deeplearning4j.earlystopping.EarlyStoppingModelSaver
-
Retrieve the most recent model that was previously saved
- getLatestModel() - Method in class org.deeplearning4j.earlystopping.saver.InMemoryModelSaver
-
- getLatestModel() - Method in class org.deeplearning4j.earlystopping.saver.LocalFileGraphSaver
-
- getLatestModel() - Method in class org.deeplearning4j.earlystopping.saver.LocalFileModelSaver
-
- getLatestUpdate(String, String, String) - Method in interface org.deeplearning4j.api.storage.StatsStorage
-
Get the latest update record (i.e., update record with the largest timestamp value) for the specified
session and worker IDs
- getLatestUpdate(String, String, String) - Method in class org.deeplearning4j.ui.storage.BaseCollectionStatsStorage
-
- getLatestUpdate(String, String, String) - Method in class org.deeplearning4j.ui.storage.sqlite.J7FileStatsStorage
-
- getLatestUpdateAllWorkers(String, String) - Method in interface org.deeplearning4j.api.storage.StatsStorage
-
Get the latest update for all workers, for the given session ID
- getLatestUpdateAllWorkers(String, String) - Method in class org.deeplearning4j.ui.storage.BaseCollectionStatsStorage
-
- getLatestUpdateAllWorkers(String, String) - Method in class org.deeplearning4j.ui.storage.sqlite.J7FileStatsStorage
-
- getLayer(int) - Method in class org.deeplearning4j.nn.graph.ComputationGraph
-
Get the layer by the number of that layer, in range 0 to getNumLayers()-1
NOTE: This is different from the internal GraphVertex index for the layer
- getLayer(String) - Method in class org.deeplearning4j.nn.graph.ComputationGraph
-
Get a given layer by name.
- getLayer() - Method in class org.deeplearning4j.nn.graph.vertex.BaseWrapperVertex
-
- getLayer() - Method in interface org.deeplearning4j.nn.graph.vertex.GraphVertex
-
Get the Layer (if any).
- getLayer() - Method in class org.deeplearning4j.nn.graph.vertex.impl.ElementWiseVertex
-
- getLayer() - Method in class org.deeplearning4j.nn.graph.vertex.impl.InputVertex
-
- getLayer() - Method in class org.deeplearning4j.nn.graph.vertex.impl.L2NormalizeVertex
-
- getLayer() - Method in class org.deeplearning4j.nn.graph.vertex.impl.L2Vertex
-
- getLayer() - Method in class org.deeplearning4j.nn.graph.vertex.impl.LayerVertex
-
- getLayer() - Method in class org.deeplearning4j.nn.graph.vertex.impl.MergeVertex
-
- getLayer() - Method in class org.deeplearning4j.nn.graph.vertex.impl.PoolHelperVertex
-
- getLayer() - Method in class org.deeplearning4j.nn.graph.vertex.impl.PreprocessorVertex
-
- getLayer() - Method in class org.deeplearning4j.nn.graph.vertex.impl.ReshapeVertex
-
- getLayer() - Method in class org.deeplearning4j.nn.graph.vertex.impl.rnn.DuplicateToTimeSeriesVertex
-
- getLayer() - Method in class org.deeplearning4j.nn.graph.vertex.impl.rnn.LastTimeStepVertex
-
- getLayer() - Method in class org.deeplearning4j.nn.graph.vertex.impl.rnn.ReverseTimeSeriesVertex
-
- getLayer() - Method in class org.deeplearning4j.nn.graph.vertex.impl.ScaleVertex
-
- getLayer() - Method in class org.deeplearning4j.nn.graph.vertex.impl.ShiftVertex
-
- getLayer() - Method in class org.deeplearning4j.nn.graph.vertex.impl.StackVertex
-
- getLayer() - Method in class org.deeplearning4j.nn.graph.vertex.impl.SubsetVertex
-
- getLayer() - Method in class org.deeplearning4j.nn.graph.vertex.impl.UnstackVertex
-
- getLayer() - Method in class org.deeplearning4j.nn.modelimport.keras.KerasLayer
-
Gets corresponding DL4J Layer, if any.
- getLayer(int) - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
-
- getLayer(String) - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
-
- getLayerActivationTypes(InputType...) - Method in class org.deeplearning4j.nn.conf.ComputationGraphConfiguration
-
For the given input shape/type for the network, return a map of activation sizes for each layer and vertex
in the graph.
- getLayerActivationTypes(boolean, InputType...) - Method in class org.deeplearning4j.nn.conf.ComputationGraphConfiguration
-
For the given input shape/type for the network, return a map of activation sizes for each layer and vertex
in the graph.
- getLayerActivationTypes() - Method in class org.deeplearning4j.nn.conf.ComputationGraphConfiguration.GraphBuilder
-
For the (perhaps partially constructed) network configuration, return a map of activation sizes for each
layer and vertex in the graph.
Note 1: The network configuration may be incomplete, but the inputs have been added to the layer already.
Note 2: To use this method, the network input types must have been set using
ComputationGraphConfiguration.GraphBuilder.setInputTypes(InputType...)
first
- getLayerActivationTypes(InputType) - Method in class org.deeplearning4j.nn.conf.MultiLayerConfiguration
-
For the given input shape/type for the network, return a list of activation sizes for each layer in the network.
i.e., list.get(i) is the output activation sizes for layer i
- getLayerActivationTypes() - Method in class org.deeplearning4j.nn.conf.NeuralNetConfiguration.ListBuilder
-
- getLayerName() - Method in class org.deeplearning4j.nn.modelimport.keras.KerasLayer
-
Get Keras layer name.
- getLayerName(MutableDirectBuffer, int, int) - Method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder.LayerNamesDecoder
-
- getLayerName(byte[], int, int) - Method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder.LayerNamesDecoder
-
- getLayerNameFromConfig(Map<String, Object>, KerasLayerConfiguration) - Static method in class org.deeplearning4j.nn.modelimport.keras.utils.KerasLayerUtils
-
Get layer name from Keras layer configuration.
- getLayerNames() - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
-
- getLayerNames() - Method in class org.deeplearning4j.ui.weights.beans.CompactModelAndGradient
-
- getLayerParams() - Method in class org.deeplearning4j.nn.conf.layers.samediff.AbstractSameDiffLayer
-
- getLayers() - Method in class org.deeplearning4j.nn.graph.ComputationGraph
-
Get all layers in the ComputationGraph
- getLayers() - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
-
- getLayerSize() - Method in class org.deeplearning4j.models.embeddings.wordvectors.WordVectorsImpl
-
This method returns word vector size
- getLayerwise() - Method in class org.deeplearning4j.nn.conf.NeuralNetConfiguration.ListBuilder
-
- getLayerWiseConfigurations() - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
-
- getLearningRate() - Method in class org.deeplearning4j.graph.models.deepwalk.DeepWalk
-
- getLearningRates() - Method in interface org.deeplearning4j.ui.stats.api.StatsReport
-
Get the learning rates by parameter
- getLearningRates() - Method in class org.deeplearning4j.ui.stats.impl.java.JavaStatsReport
-
- getLearningRates() - Method in class org.deeplearning4j.ui.stats.impl.SbeStatsReport
-
- getLeaves() - Method in class org.deeplearning4j.clustering.randomprojection.RPTree
-
- getLeaves() - Method in class org.deeplearning4j.nn.layers.feedforward.autoencoder.recursive.Tree
-
Gets the leaves of the tree.
- getLeaves(List<T>) - Method in class org.deeplearning4j.nn.layers.feedforward.autoencoder.recursive.Tree
-
Gets the leaves of the tree.
- getLeft() - Method in class com.atilika.kuromoji.trie.PatriciaTrie.PatriciaNode
-
Returns this node's left node
- getLeft() - Method in class org.deeplearning4j.clustering.kdtree.KDTree.KDNode
-
- getLeftId(int) - Method in interface com.atilika.kuromoji.dict.Dictionary
-
Gets the left id of the specified word
- getLeftId() - Method in class com.atilika.kuromoji.dict.DictionaryEntryBase
-
- getLeftId(int) - Method in class com.atilika.kuromoji.dict.InsertedDictionary
-
- getLeftId(int) - Method in class com.atilika.kuromoji.dict.TokenInfoDictionary
-
- getLeftId(int) - Method in class com.atilika.kuromoji.dict.UnknownDictionary
-
- getLeftId(int) - Method in class com.atilika.kuromoji.dict.UserDictionary
-
- getLeftId() - Method in class com.atilika.kuromoji.viterbi.ViterbiNode
-
- getLeftNode() - Method in class com.atilika.kuromoji.viterbi.ViterbiNode
-
- getLegacyJsonMapper() - Method in class org.deeplearning4j.nn.conf.serde.legacyformat.LegacyGraphVertexDeserializer
-
- getLegacyJsonMapper() - Method in class org.deeplearning4j.nn.conf.serde.legacyformat.LegacyLayerDeserializer
-
- getLegacyJsonMapper() - Method in class org.deeplearning4j.nn.conf.serde.legacyformat.LegacyPreprocessorDeserializer
-
- getLegacyJsonMapper() - Method in class org.deeplearning4j.nn.conf.serde.legacyformat.LegacyReconstructionDistributionDeserializer
-
- getLegacyNamesMap() - Method in class org.deeplearning4j.nn.conf.serde.legacyformat.LegacyGraphVertexDeserializer
-
- getLegacyNamesMap() - Method in class org.deeplearning4j.nn.conf.serde.legacyformat.LegacyLayerDeserializer
-
- getLegacyNamesMap() - Method in class org.deeplearning4j.nn.conf.serde.legacyformat.LegacyPreprocessorDeserializer
-
- getLegacyNamesMap() - Method in class org.deeplearning4j.nn.conf.serde.legacyformat.LegacyReconstructionDistributionDeserializer
-
- getListeners() - Method in interface org.deeplearning4j.api.storage.StatsStorage
-
Get a list (shallow copy) of all listeners currently present
- getListeners() - Method in interface org.deeplearning4j.nn.api.Layer
-
Get the iteration listeners for this layer.
- getListeners() - Method in class org.deeplearning4j.nn.graph.ComputationGraph
-
Get the trainingListeners for the ComputationGraph
- getListeners() - Method in class org.deeplearning4j.nn.layers.AbstractLayer
-
- getListeners() - Method in class org.deeplearning4j.nn.layers.normalization.BatchNormalization
-
- getListeners() - Method in class org.deeplearning4j.nn.layers.recurrent.BidirectionalLayer
-
- getListeners() - Method in class org.deeplearning4j.nn.layers.variational.VariationalAutoencoder
-
- getListeners() - Method in class org.deeplearning4j.nn.layers.wrapper.BaseWrapperLayer
-
- getListeners() - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
-
- getListeners() - Method in class org.deeplearning4j.spark.datavec.iterator.SparkSourceDummyReader
-
- getListeners() - Method in class org.deeplearning4j.ui.storage.BaseCollectionStatsStorage
-
- getListeners() - Method in class org.deeplearning4j.ui.storage.sqlite.J7FileStatsStorage
-
- getLocalResponseNormalization() - Method in class org.deeplearning4j.nn.modelimport.keras.layers.custom.KerasLRN
-
Get DL4J LRN.
- getLog(Class<?>) - Static method in class org.ansj.util.MyStaticValue
-
- getLog() - Static method in class org.deeplearning4j.spark.models.embeddings.word2vec.Word2VecParam
-
Deprecated.
- getLog() - Static method in class org.deeplearning4j.spark.models.embeddings.word2vec.Word2VecPerformerVoid
-
Deprecated.
- getLongHash(String) - Static method in class org.deeplearning4j.models.sequencevectors.sequence.SequenceElement
-
- getLossFn() - Method in class org.deeplearning4j.nn.conf.ocnn.OCNNOutputLayer
-
- getLossLayer(InputType) - Method in class org.deeplearning4j.nn.modelimport.keras.layers.KerasLoss
-
Get DL4J LossLayer.
- getLower(INDArray, int) - Method in class org.deeplearning4j.clustering.kdtree.HyperRect
-
- getLower() - Method in class org.deeplearning4j.nn.conf.distribution.UniformDistribution
-
- getLr() - Method in class org.deeplearning4j.models.embeddings.inmemory.InMemoryLookupTable
-
Deprecated.
- getLr() - Method in class org.deeplearning4j.spark.models.embeddings.glove.GloveParam
-
- getLSTMLayer() - Method in class org.deeplearning4j.nn.modelimport.keras.layers.recurrent.KerasLstm
-
Get DL4J Layer.
- getMachineID() - Method in class org.deeplearning4j.spark.stats.BaseEventStats
-
- getMachineID() - Method in interface org.deeplearning4j.spark.stats.EventStats
-
- getMagicNumber() - Method in class org.deeplearning4j.datasets.mnist.MnistDbFile
-
MNIST DB files start with unique integer number.
- getMagicNumber() - Method in class org.deeplearning4j.datasets.mnist.MnistImageFile
-
- getMagicNumber() - Method in class org.deeplearning4j.datasets.mnist.MnistLabelFile
-
- getMapper() - Static method in class org.deeplearning4j.nn.conf.serde.JsonMappers
-
- getMapperYaml() - Static method in class org.deeplearning4j.nn.conf.serde.JsonMappers
-
- getMask() - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
-
- getMaskArray() - Method in interface org.deeplearning4j.nn.api.Layer
-
- getMaskArray() - Method in class org.deeplearning4j.nn.layers.AbstractLayer
-
- getMaskArray() - Method in class org.deeplearning4j.nn.layers.recurrent.BidirectionalLayer
-
- getMaskArray() - Method in class org.deeplearning4j.nn.layers.variational.VariationalAutoencoder
-
- getMaskArray() - Method in class org.deeplearning4j.nn.layers.wrapper.BaseWrapperLayer
-
- getMaskArray() - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
-
- getMatchLength() - Method in class com.atilika.kuromoji.dict.UserDictionary.UserDictionaryMatch
-
- getMatchStartIndex() - Method in class com.atilika.kuromoji.dict.UserDictionary.UserDictionaryMatch
-
- getMAX_EXP() - Static method in class org.deeplearning4j.spark.models.embeddings.word2vec.Word2VecPerformerVoid
-
Deprecated.
- getMaxCount() - Method in class org.deeplearning4j.models.glove.GloveWeightLookupTable
-
Deprecated.
- getMaxCount() - Method in class org.deeplearning4j.spark.models.embeddings.glove.GloveParam
-
- getMaxIterations() - Method in class org.deeplearning4j.optimize.solvers.BackTrackLineSearch
-
- getMean() - Method in class org.deeplearning4j.nn.conf.distribution.LogNormalDistribution
-
- getMean() - Method in class org.deeplearning4j.nn.conf.distribution.NormalDistribution
-
- getMean() - Method in class org.deeplearning4j.nn.conf.distribution.TruncatedNormalDistribution
-
- getMean(StatsType) - Method in interface org.deeplearning4j.ui.stats.api.StatsReport
-
Get the mean values for each parameter for the given StatsType (Parameters/Updates/Activations)
- getMean(StatsType) - Method in class org.deeplearning4j.ui.stats.impl.java.JavaStatsReport
-
- getMean(StatsType) - Method in class org.deeplearning4j.ui.stats.impl.SbeStatsReport
-
- getMeanMagnitudes(StatsType) - Method in interface org.deeplearning4j.ui.stats.api.StatsReport
-
Get the mean magnitude values for each parameter for the given StatsType (Parameters/Updates/Activations)
- getMeanMagnitudes(StatsType) - Method in class org.deeplearning4j.ui.stats.impl.java.JavaStatsReport
-
- getMeanMagnitudes(StatsType) - Method in class org.deeplearning4j.ui.stats.impl.SbeStatsReport
-
- getMedian() - Method in class org.deeplearning4j.text.movingwindow.Window
-
- getMemoryBytes(MemoryType, int, MemoryUseMode, CacheMode, DataBuffer.Type) - Method in class org.deeplearning4j.nn.conf.memory.LayerMemoryReport
-
- getMemoryBytes(MemoryType, int, MemoryUseMode, CacheMode) - Method in class org.deeplearning4j.nn.conf.memory.MemoryReport
-
Get the memory estimate (in bytes) for the specified type of memory, using the current ND4J data type
- getMemoryBytes(MemoryType, int, MemoryUseMode, CacheMode, DataBuffer.Type) - Method in class org.deeplearning4j.nn.conf.memory.MemoryReport
-
Get the memory estimate (in bytes) for the specified type of memory
- getMemoryBytes(MemoryType, int, MemoryUseMode, CacheMode, DataBuffer.Type) - Method in class org.deeplearning4j.nn.conf.memory.NetworkMemoryReport
-
- getMemoryFootprint() - Method in class org.deeplearning4j.models.glove.AbstractCoOccurrences
-
This method returns estimated memory footrpint, based on current CountMap content
- getMemoryReport(InputType...) - Method in class org.deeplearning4j.nn.conf.ComputationGraphConfiguration
-
Get a
MemoryReport for the given computation graph configuration.
- getMemoryReport(InputType...) - Method in class org.deeplearning4j.nn.conf.graph.ElementWiseVertex
-
- getMemoryReport(InputType...) - Method in class org.deeplearning4j.nn.conf.graph.FrozenVertex
-
- getMemoryReport(InputType...) - Method in class org.deeplearning4j.nn.conf.graph.GraphVertex
-
This is a report of the estimated memory consumption for the given vertex
- getMemoryReport(InputType...) - Method in class org.deeplearning4j.nn.conf.graph.L2NormalizeVertex
-
- getMemoryReport(InputType...) - Method in class org.deeplearning4j.nn.conf.graph.L2Vertex
-
- getMemoryReport(InputType...) - Method in class org.deeplearning4j.nn.conf.graph.LayerVertex
-
- getMemoryReport(InputType...) - Method in class org.deeplearning4j.nn.conf.graph.MergeVertex
-
- getMemoryReport(InputType...) - Method in class org.deeplearning4j.nn.conf.graph.PoolHelperVertex
-
- getMemoryReport(InputType...) - Method in class org.deeplearning4j.nn.conf.graph.PreprocessorVertex
-
- getMemoryReport(InputType...) - Method in class org.deeplearning4j.nn.conf.graph.ReshapeVertex
-
- getMemoryReport(InputType...) - Method in class org.deeplearning4j.nn.conf.graph.rnn.DuplicateToTimeSeriesVertex
-
- getMemoryReport(InputType...) - Method in class org.deeplearning4j.nn.conf.graph.rnn.LastTimeStepVertex
-
- getMemoryReport(InputType...) - Method in class org.deeplearning4j.nn.conf.graph.rnn.ReverseTimeSeriesVertex
-
- getMemoryReport(InputType...) - Method in class org.deeplearning4j.nn.conf.graph.ScaleVertex
-
- getMemoryReport(InputType...) - Method in class org.deeplearning4j.nn.conf.graph.ShiftVertex
-
- getMemoryReport(InputType...) - Method in class org.deeplearning4j.nn.conf.graph.StackVertex
-
- getMemoryReport(InputType...) - Method in class org.deeplearning4j.nn.conf.graph.SubsetVertex
-
- getMemoryReport(InputType...) - Method in class org.deeplearning4j.nn.conf.graph.UnstackVertex
-
- getMemoryReport(InputType) - Method in class org.deeplearning4j.nn.conf.layers.ActivationLayer
-
- getMemoryReport(InputType) - Method in class org.deeplearning4j.nn.conf.layers.AutoEncoder
-
- getMemoryReport(InputType) - Method in class org.deeplearning4j.nn.conf.layers.BaseOutputLayer
-
- getMemoryReport(InputType) - Method in class org.deeplearning4j.nn.conf.layers.BatchNormalization
-
- getMemoryReport(InputType) - Method in class org.deeplearning4j.nn.conf.layers.CenterLossOutputLayer
-
- getMemoryReport(InputType) - Method in class org.deeplearning4j.nn.conf.layers.CnnLossLayer
-
- getMemoryReport(InputType) - Method in class org.deeplearning4j.nn.conf.layers.convolutional.Cropping1D
-
- getMemoryReport(InputType) - Method in class org.deeplearning4j.nn.conf.layers.convolutional.Cropping2D
-
- getMemoryReport(InputType) - Method in class org.deeplearning4j.nn.conf.layers.convolutional.Cropping3D
-
- getMemoryReport(InputType) - Method in class org.deeplearning4j.nn.conf.layers.ConvolutionLayer
-
- getMemoryReport(InputType) - Method in class org.deeplearning4j.nn.conf.layers.DenseLayer
-
- getMemoryReport(InputType) - Method in class org.deeplearning4j.nn.conf.layers.DropoutLayer
-
- getMemoryReport(InputType) - Method in class org.deeplearning4j.nn.conf.layers.EmbeddingLayer
-
- getMemoryReport(InputType) - Method in class org.deeplearning4j.nn.conf.layers.EmbeddingSequenceLayer
-
- getMemoryReport(InputType) - Method in class org.deeplearning4j.nn.conf.layers.GlobalPoolingLayer
-
- getMemoryReport(InputType) - Method in class org.deeplearning4j.nn.conf.layers.GravesBidirectionalLSTM
-
Deprecated.
- getMemoryReport(InputType) - Method in class org.deeplearning4j.nn.conf.layers.GravesLSTM
-
- getMemoryReport(InputType) - Method in class org.deeplearning4j.nn.conf.layers.Layer
-
This is a report of the estimated memory consumption for the given layer
- getMemoryReport(InputType) - Method in class org.deeplearning4j.nn.conf.layers.LocalResponseNormalization
-
- getMemoryReport(InputType) - Method in class org.deeplearning4j.nn.conf.layers.LossLayer
-
- getMemoryReport(InputType) - Method in class org.deeplearning4j.nn.conf.layers.LSTM
-
- getMemoryReport(InputType) - Method in class org.deeplearning4j.nn.conf.layers.misc.ElementWiseMultiplicationLayer
-
This is a report of the estimated memory consumption for the given layer
- getMemoryReport(InputType) - Method in class org.deeplearning4j.nn.conf.layers.misc.FrozenLayer
-
- getMemoryReport(InputType) - Method in class org.deeplearning4j.nn.conf.layers.objdetect.Yolo2OutputLayer
-
- getMemoryReport(InputType) - Method in class org.deeplearning4j.nn.conf.layers.recurrent.Bidirectional
-
- getMemoryReport(InputType) - Method in class org.deeplearning4j.nn.conf.layers.recurrent.SimpleRnn
-
- getMemoryReport(InputType) - Method in class org.deeplearning4j.nn.conf.layers.RnnLossLayer
-
- getMemoryReport(InputType) - Method in class org.deeplearning4j.nn.conf.layers.samediff.AbstractSameDiffLayer
-
- getMemoryReport(InputType) - Method in class org.deeplearning4j.nn.conf.layers.SpaceToBatchLayer
-
- getMemoryReport(InputType) - Method in class org.deeplearning4j.nn.conf.layers.SpaceToDepthLayer
-
- getMemoryReport(InputType) - Method in class org.deeplearning4j.nn.conf.layers.Subsampling3DLayer
-
- getMemoryReport(InputType) - Method in class org.deeplearning4j.nn.conf.layers.SubsamplingLayer
-
- getMemoryReport(InputType) - Method in class org.deeplearning4j.nn.conf.layers.Upsampling1D
-
- getMemoryReport(InputType) - Method in class org.deeplearning4j.nn.conf.layers.Upsampling2D
-
- getMemoryReport(InputType) - Method in class org.deeplearning4j.nn.conf.layers.Upsampling3D
-
- getMemoryReport(InputType) - Method in class org.deeplearning4j.nn.conf.layers.util.MaskLayer
-
- getMemoryReport(InputType) - Method in class org.deeplearning4j.nn.conf.layers.util.MaskZeroLayer
-
- getMemoryReport(InputType) - Method in class org.deeplearning4j.nn.conf.layers.variational.VariationalAutoencoder
-
- getMemoryReport(InputType) - Method in class org.deeplearning4j.nn.conf.layers.wrapper.BaseWrapperLayer
-
- getMemoryReport(InputType) - Method in class org.deeplearning4j.nn.conf.layers.ZeroPadding1DLayer
-
- getMemoryReport(InputType) - Method in class org.deeplearning4j.nn.conf.layers.ZeroPadding3DLayer
-
- getMemoryReport(InputType) - Method in class org.deeplearning4j.nn.conf.layers.ZeroPaddingLayer
-
- getMemoryReport(InputType) - Method in class org.deeplearning4j.nn.conf.MultiLayerConfiguration
-
- getMemoryReport(AbstractLSTM, InputType) - Static method in class org.deeplearning4j.nn.layers.recurrent.LSTMHelpers
-
- getMemoryReport(GravesBidirectionalLSTM, InputType) - Static method in class org.deeplearning4j.nn.layers.recurrent.LSTMHelpers
-
- getMemoryReport(boolean, FeedForwardLayer, InputType) - Static method in class org.deeplearning4j.nn.layers.recurrent.LSTMHelpers
-
- getMemoryThreshold() - Method in class org.deeplearning4j.models.glove.AbstractCoOccurrences
-
This memory returns memory threshold, defined as 1/2 of memory allowed for allocation
- getMessage(String) - Method in interface org.deeplearning4j.ui.api.I18N
-
- getMessage(String, String) - Method in interface org.deeplearning4j.ui.api.I18N
-
Get the specified message for the specified language
- getMessage(String) - Method in class org.deeplearning4j.ui.i18n.DefaultI18N
-
- getMessage(String, String) - Method in class org.deeplearning4j.ui.i18n.DefaultI18N
-
- getMinAlpha() - Method in class org.deeplearning4j.spark.models.embeddings.word2vec.Word2VecParam
-
Deprecated.
- getMinAlpha() - Method in class org.deeplearning4j.spark.models.embeddings.word2vec.Word2VecPerformerVoid
-
Deprecated.
- getMinibatchesPerSecond() - Method in interface org.deeplearning4j.ui.stats.api.StatsReport
-
Get the number of minibatches per second, since the last report
- getModel() - Method in class org.deeplearning4j.parallelism.parameterserver.ParameterServerTrainer
-
- getModel() - Method in class org.deeplearning4j.parallelism.trainer.DefaultTrainer
-
- getModel() - Method in interface org.deeplearning4j.parallelism.trainer.Trainer
-
THe current model for the trainer
- getModelClassName() - Method in interface org.deeplearning4j.ui.stats.api.StatsInitializationReport
-
- getModelConfigClassName(MutableDirectBuffer, int, int) - Method in class org.deeplearning4j.ui.stats.sbe.StaticInfoDecoder
-
- getModelConfigClassName(byte[], int, int) - Method in class org.deeplearning4j.ui.stats.sbe.StaticInfoDecoder
-
- getModelConfigJson() - Method in interface org.deeplearning4j.ui.stats.api.StatsInitializationReport
-
- getModelConfigJson(MutableDirectBuffer, int, int) - Method in class org.deeplearning4j.ui.stats.sbe.StaticInfoDecoder
-
- getModelConfigJson(byte[], int, int) - Method in class org.deeplearning4j.ui.stats.sbe.StaticInfoDecoder
-
- getModelNumLayers() - Method in interface org.deeplearning4j.ui.stats.api.StatsInitializationReport
-
- getModelNumParams() - Method in interface org.deeplearning4j.ui.stats.api.StatsInitializationReport
-
- getModelParamNames() - Method in interface org.deeplearning4j.ui.stats.api.StatsInitializationReport
-
- getModelParamNames(MutableDirectBuffer, int, int) - Method in class org.deeplearning4j.ui.stats.sbe.StaticInfoDecoder.ModelParamNamesDecoder
-
- getModelParamNames(byte[], int, int) - Method in class org.deeplearning4j.ui.stats.sbe.StaticInfoDecoder.ModelParamNamesDecoder
-
- getModelType(Model) - Static method in class org.deeplearning4j.optimize.listeners.checkpoint.CheckpointListener
-
- getModuleName() - Method in interface org.deeplearning4j.nn.conf.module.GraphBuilderModule
-
A module should return its name.
- getModuleName() - Static method in class org.deeplearning4j.zoo.model.helper.FaceNetHelper
-
- getModuleName(String) - Static method in class org.deeplearning4j.zoo.model.helper.FaceNetHelper
-
- getMostPopulatedClusters(int) - Method in class org.deeplearning4j.clustering.cluster.ClusterSet
-
- getMostRecentClusterSetInfo() - Method in class org.deeplearning4j.clustering.iteration.IterationHistory
-
- getMostRecentIterationInfo() - Method in class org.deeplearning4j.clustering.iteration.IterationHistory
-
- getMostSpreadOutClusters(ClusterSet, ClusterSetInfo, int) - Static method in class org.deeplearning4j.clustering.cluster.ClusterUtils
-
- getMultiLayerConfiguration() - Method in class org.deeplearning4j.nn.modelimport.keras.KerasSequentialModel
-
Configure a MultiLayerConfiguration from this Keras Sequential model configuration.
- getMultiLayerNetwork() - Method in class org.deeplearning4j.nn.modelimport.keras.KerasSequentialModel
-
Build a MultiLayerNetwork from this Keras Sequential model configuration.
- getMultiLayerNetwork(boolean) - Method in class org.deeplearning4j.nn.modelimport.keras.KerasSequentialModel
-
Build a MultiLayerNetwork from this Keras Sequential model configuration and import weights.
- getName() - Method in class org.ansj.app.crf.pojo.Element
-
- getName() - Method in class org.ansj.app.keyword.Keyword
-
- getName() - Method in class org.ansj.domain.NewWord
-
- getName() - Method in class org.ansj.domain.Term
-
- getName() - Method in class org.deeplearning4j.base.EmnistFetcher
-
- getName() - Method in class org.deeplearning4j.base.MnistFetcher
-
- getName() - Method in class org.deeplearning4j.nn.conf.memory.LayerMemoryReport
-
- getName() - Method in class org.deeplearning4j.nn.conf.memory.MemoryReport
-
Name of the object that the memory report was generated for
- getName() - Method in class org.deeplearning4j.nn.conf.memory.NetworkMemoryReport
-
- getNameIfOutArr(List<Element>, int) - Method in class org.ansj.app.crf.Config
-
- getNameLabel(String) - Method in class org.deeplearning4j.datasets.rearrange.LocalUnstructuredDataFormatter
-
- getNature() - Method in class org.ansj.domain.NewWord
-
- getNature(String) - Static method in class org.ansj.library.NatureLibrary
-
根据字符串得道词性.没有就创建一个
- getNatureClassSuffix() - Static method in class org.ansj.util.MyStaticValue
-
得道姓名单字的词频词典
- getNatureMapReader() - Static method in class org.ansj.util.MyStaticValue
-
词性表
- getNatureStr() - Method in class org.ansj.domain.Term
-
- getNatureTableReader() - Static method in class org.ansj.util.MyStaticValue
-
词性关联表
- getNegative() - Method in class org.deeplearning4j.models.embeddings.inmemory.InMemoryLookupTable
-
- getNegative() - Method in class org.deeplearning4j.spark.models.embeddings.glove.GloveParam
-
- getNegative() - Method in class org.deeplearning4j.spark.models.embeddings.word2vec.Word2VecParam
-
Deprecated.
- getNegative() - Method in class org.deeplearning4j.spark.models.embeddings.word2vec.Word2VecPerformerVoid
-
Deprecated.
- getNestedTrainingStats() - Method in class org.deeplearning4j.spark.api.stats.CommonSparkTrainingStats
-
- getNestedTrainingStats() - Method in interface org.deeplearning4j.spark.api.stats.SparkTrainingStats
-
Return the nested training stats - if any.
- getNestedTrainingStats() - Method in class org.deeplearning4j.spark.impl.paramavg.stats.ParameterAveragingTrainingMasterStats
-
- getNestedTrainingStats() - Method in class org.deeplearning4j.spark.impl.paramavg.stats.ParameterAveragingTrainingWorkerStats
-
- getNetwork() - Method in class org.deeplearning4j.spark.impl.graph.SparkComputationGraph
-
- getNetwork() - Method in class org.deeplearning4j.spark.impl.multilayer.SparkDl4jMultiLayer
-
- getNewDestination(String, boolean) - Method in class org.deeplearning4j.datasets.rearrange.LocalUnstructuredDataFormatter
-
- getNewInitializationReport() - Method in class org.deeplearning4j.ui.stats.BaseStatsListener
-
- getNewInitializationReport() - Method in class org.deeplearning4j.ui.stats.J7StatsListener
-
- getNewInitializationReport() - Method in class org.deeplearning4j.ui.stats.StatsListener
-
- getNewMapper(JsonFactory) - Static method in class org.deeplearning4j.spark.impl.paramavg.BaseTrainingMaster
-
- getNewStatsReport() - Method in class org.deeplearning4j.ui.stats.BaseStatsListener
-
- getNewStatsReport() - Method in class org.deeplearning4j.ui.stats.J7StatsListener
-
- getNewStatsReport() - Method in class org.deeplearning4j.ui.stats.StatsListener
-
- getNewStorageMetaData(long, String, String) - Method in class org.deeplearning4j.ui.stats.BaseStatsListener
-
- getNewStorageMetaData(long, String, String) - Method in class org.deeplearning4j.ui.stats.J7StatsListener
-
- getNewStorageMetaData(long, String, String) - Method in class org.deeplearning4j.ui.stats.StatsListener
-
- getNewTerms() - Method in class org.ansj.recognition.arrimpl.AsianPersonRecognition
-
- getNewTerms() - Method in class org.ansj.recognition.arrimpl.ForeignPersonRecognition
-
- getNewWordReader() - Static method in class org.ansj.util.MyStaticValue
-
机构名词典
- getNewWords(Term[]) - Method in class org.ansj.recognition.arrimpl.AsianPersonRecognition
-
- getNewWords(Term[]) - Method in class org.ansj.recognition.arrimpl.ForeignPersonRecognition
-
- getNextRandom() - Method in class org.deeplearning4j.spark.models.embeddings.word2vec.Word2VecParam
-
Deprecated.
- getNextRandom() - Method in class org.deeplearning4j.spark.models.embeddings.word2vec.Word2VecPerformerVoid
-
Deprecated.
- getnLayers() - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
-
Get the number of layers in the network
- getNorthEast() - Method in class org.deeplearning4j.clustering.quadtree.QuadTree
-
- getNorthWest() - Method in class org.deeplearning4j.clustering.quadtree.QuadTree
-
- getNOut() - Method in class org.deeplearning4j.nn.conf.ocnn.OCNNOutputLayer
-
- getNOutFromConfig(Map<String, Object>, KerasLayerConfiguration) - Static method in class org.deeplearning4j.nn.modelimport.keras.utils.KerasLayerUtils
-
Get number of outputs from Keras layer configuration.
- getNum(String) - Static method in class org.ansj.app.crf.Config
-
- getNumberOfLabelsUsed() - Method in class org.deeplearning4j.text.documentiterator.LabelsSource
-
This method returns number of labels used up to the method's call
- getNumberOfSequences() - Method in class org.deeplearning4j.models.word2vec.wordstore.VocabConstructor
-
This method returns total number of sequences passed through VocabConstructor
- getNumberOfTrials() - Method in class org.deeplearning4j.nn.conf.distribution.BinomialDistribution
-
- getNumberReader() - Static method in class org.ansj.util.MyStaticValue
-
数字词典
- getNumChildren() - Method in class org.deeplearning4j.clustering.sptree.SpTree
-
- getNumClasses() - Method in class org.deeplearning4j.eval.ROCMultiClass
-
- getNumDataSetObjectsPerSplit(int) - Method in class org.deeplearning4j.spark.impl.paramavg.ParameterAveragingTrainingMaster
-
- getNumDataSetObjectsPerSplit(int) - Method in class org.deeplearning4j.spark.parameterserver.training.SharedTrainingMaster
-
- getNumDataSets() - Method in class org.deeplearning4j.datasets.test.TestDataSetIterator
-
- getNumDimensions() - Method in class org.deeplearning4j.plot.BarnesHutTsne
-
- getNumExamplesTotal() - Method in class org.deeplearning4j.datasets.rearrange.LocalUnstructuredDataFormatter
-
- getNumExamplesToTrainOn() - Method in class org.deeplearning4j.datasets.rearrange.LocalUnstructuredDataFormatter
-
- getNumInputArrays() - Method in class org.deeplearning4j.nn.graph.ComputationGraph
-
The number of inputs to this network
- getNumInputArrays() - Method in class org.deeplearning4j.nn.graph.vertex.BaseGraphVertex
-
- getNumInputArrays() - Method in class org.deeplearning4j.nn.graph.vertex.BaseWrapperVertex
-
- getNumInputArrays() - Method in interface org.deeplearning4j.nn.graph.vertex.GraphVertex
-
Get the number of input arrays.
- getNumLayers() - Method in class org.deeplearning4j.nn.graph.ComputationGraph
-
Returns the number of layers in the ComputationGraph
- getNumOutputArrays() - Method in class org.deeplearning4j.nn.graph.ComputationGraph
-
The number of output (arrays) for this network
- getNumOutputConnections() - Method in class org.deeplearning4j.nn.graph.vertex.BaseGraphVertex
-
- getNumOutputConnections() - Method in class org.deeplearning4j.nn.graph.vertex.BaseWrapperVertex
-
- getNumOutputConnections() - Method in interface org.deeplearning4j.nn.graph.vertex.GraphVertex
-
Get the number of outgoing connections from this GraphVertex.
- getNumParams() - Method in class org.deeplearning4j.nn.modelimport.keras.KerasLayer
-
Returns number of trainable parameters in layer.
- getNumParams() - Method in class org.deeplearning4j.nn.modelimport.keras.layers.convolutional.KerasConvolution
-
Returns number of trainable parameters in layer.
- getNumParams() - Method in class org.deeplearning4j.nn.modelimport.keras.layers.core.KerasDense
-
Returns number of trainable parameters in layer.
- getNumParams() - Method in class org.deeplearning4j.nn.modelimport.keras.layers.embeddings.KerasEmbedding
-
Returns number of trainable parameters in layer.
- getNumParams() - Method in class org.deeplearning4j.nn.modelimport.keras.layers.normalization.KerasBatchNormalization
-
Returns number of trainable parameters in layer.
- getNumParams() - Method in class org.deeplearning4j.nn.modelimport.keras.layers.recurrent.KerasLstm
-
Returns number of trainable parameters in layer.
- getNumParams() - Method in class org.deeplearning4j.nn.modelimport.keras.layers.recurrent.KerasSimpleRnn
-
Returns number of trainable parameters in layer.
- getNumParams() - Method in class org.deeplearning4j.nn.modelimport.keras.layers.wrappers.KerasBidirectional
-
Returns number of trainable parameters in layer.
- getNumRowCounter() - Method in class org.deeplearning4j.eval.Evaluation
-
- getNumTables() - Method in interface org.deeplearning4j.clustering.lsh.LSH
-
denoting numTables by n,
amplifies a (d1, d2, p1, p2) hash family into a
(d1, d2, (1-p1^n), (1-p2^n))-sensitive one (match probability is increasing with n)
- getNumTestExamples() - Method in class org.deeplearning4j.datasets.rearrange.LocalUnstructuredDataFormatter
-
- getNumUpdateRecordsFor(String) - Method in interface org.deeplearning4j.api.storage.StatsStorage
-
Return the number of update records for the given session ID (all workers)
- getNumUpdateRecordsFor(String, String, String) - Method in interface org.deeplearning4j.api.storage.StatsStorage
-
Return the number of update records for the given session ID and worker ID
- getNumUpdateRecordsFor(String) - Method in class org.deeplearning4j.ui.storage.BaseCollectionStatsStorage
-
- getNumUpdateRecordsFor(String, String, String) - Method in class org.deeplearning4j.ui.storage.BaseCollectionStatsStorage
-
- getNumUpdateRecordsFor(String) - Method in class org.deeplearning4j.ui.storage.sqlite.J7FileStatsStorage
-
- getNumUpdateRecordsFor(String, String, String) - Method in class org.deeplearning4j.ui.storage.sqlite.J7FileStatsStorage
-
- getNumVertices() - Method in interface org.deeplearning4j.graph.models.embeddings.GraphVectorLookupTable
-
Returns the number of vertices in the graph
- getNumVertices() - Method in class org.deeplearning4j.graph.models.embeddings.InMemoryGraphLookupTable
-
- getNumWords() - Method in class org.deeplearning4j.spark.models.embeddings.word2vec.Word2VecParam
-
Deprecated.
- getNumWords() - Method in class org.deeplearning4j.spark.models.embeddings.word2vec.Word2VecPerformerVoid
-
Deprecated.
- getNumWords() - Method in class org.deeplearning4j.ui.nearestneighbors.word2vec.NearestNeighborsQuery
-
- getObjectFromFile(File, String) - Static method in class org.deeplearning4j.util.ModelSerializer
-
- getOffe() - Method in class org.ansj.domain.Term
-
- getOffe() - Method in interface org.ansj.splitWord.GetWords
-
- getOffe() - Method in class org.ansj.splitWord.impl.GetWordsImpl
-
- getOffHeapCurrentBytes() - Method in interface org.deeplearning4j.ui.stats.api.StatsReport
-
Get off-heap memory - current bytes used
- getOffHeapMaxBytes() - Method in interface org.deeplearning4j.ui.stats.api.StatsReport
-
Get off-heap memory - max available bytes
- getOp(String, INDArray, INDArray, INDArray) - Static method in class org.deeplearning4j.clustering.randomprojection.RPUtils
-
- getOptimalBufferSize(int, int, int) - Static method in class org.deeplearning4j.optimize.solvers.accumulation.EncodedGradientsAccumulator
-
This method returns optimal bufferSize for a given model
We know, that updates are guaranteed to have MAX size of params / 16.
- getOptimalBufferSize(Model, int, int) - Static method in class org.deeplearning4j.optimize.solvers.accumulation.EncodedGradientsAccumulator
-
- getOptimizer() - Method in interface org.deeplearning4j.nn.api.Model
-
Returns this models optimizer
- getOptimizer() - Method in interface org.deeplearning4j.nn.api.NeuralNetwork
-
This method returns Optimizer used for training
- getOptimizer() - Method in class org.deeplearning4j.nn.graph.ComputationGraph
-
- getOptimizer() - Method in class org.deeplearning4j.nn.layers.AbstractLayer
-
- getOptimizer() - Method in class org.deeplearning4j.nn.layers.BaseLayer
-
- getOptimizer() - Method in class org.deeplearning4j.nn.layers.recurrent.BidirectionalLayer
-
- getOptimizer() - Method in class org.deeplearning4j.nn.layers.variational.VariationalAutoencoder
-
- getOptimizer() - Method in class org.deeplearning4j.nn.layers.wrapper.BaseWrapperLayer
-
- getOptimizer() - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
-
- getOptimizer() - Method in class org.deeplearning4j.optimize.Solver
-
- getOptimizer() - Method in class org.deeplearning4j.plot.BarnesHutTsne
-
- getOrderedLayers() - Method in class org.deeplearning4j.nn.updater.BaseMultiLayerUpdater
-
- getOrderedLayers() - Method in class org.deeplearning4j.nn.updater.graph.ComputationGraphUpdater
-
- getOrderedLayers() - Method in class org.deeplearning4j.nn.updater.LayerUpdater
-
- getOrderedLayers() - Method in class org.deeplearning4j.nn.updater.MultiLayerUpdater
-
- getOutput() - Method in interface org.deeplearning4j.parallelism.inference.InferenceObservable
-
- getOutput() - Method in class org.deeplearning4j.parallelism.inference.observers.BasicInferenceObservable
-
- getOutput() - Method in class org.deeplearning4j.parallelism.inference.observers.BatchedInferenceObservable
-
- getOutputLayer(int) - Method in class org.deeplearning4j.nn.graph.ComputationGraph
-
Get the specified output layer, by index.
- getOutputLayer() - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
-
Get the output layer
- getOutputLayerIndices() - Method in class org.deeplearning4j.nn.graph.ComputationGraph
-
- getOutputs() - Method in class org.deeplearning4j.parallelism.inference.observers.BatchedInferenceObservable
-
PLEASE NOTE: This method is for tests only
- getOutputSize(INDArray, int[], int[], int[], ConvolutionMode) - Static method in class org.deeplearning4j.util.ConvolutionUtils
-
- getOutputSize(INDArray, int[], int[], int[], ConvolutionMode, int[]) - Static method in class org.deeplearning4j.util.ConvolutionUtils
-
Get the output size (height/width) for the given input data and CNN configuration
- getOutputType(int, InputType...) - Method in class org.deeplearning4j.nn.conf.graph.ElementWiseVertex
-
- getOutputType(int, InputType...) - Method in class org.deeplearning4j.nn.conf.graph.FrozenVertex
-
- getOutputType(int, InputType...) - Method in class org.deeplearning4j.nn.conf.graph.GraphVertex
-
Determine the type of output for this GraphVertex, given the specified inputs.
- getOutputType(int, InputType...) - Method in class org.deeplearning4j.nn.conf.graph.L2NormalizeVertex
-
- getOutputType(int, InputType...) - Method in class org.deeplearning4j.nn.conf.graph.L2Vertex
-
- getOutputType(int, InputType...) - Method in class org.deeplearning4j.nn.conf.graph.LayerVertex
-
- getOutputType(int, InputType...) - Method in class org.deeplearning4j.nn.conf.graph.MergeVertex
-
- getOutputType(int, InputType...) - Method in class org.deeplearning4j.nn.conf.graph.PoolHelperVertex
-
- getOutputType(int, InputType...) - Method in class org.deeplearning4j.nn.conf.graph.PreprocessorVertex
-
- getOutputType(int, InputType...) - Method in class org.deeplearning4j.nn.conf.graph.ReshapeVertex
-
- getOutputType(int, InputType...) - Method in class org.deeplearning4j.nn.conf.graph.rnn.DuplicateToTimeSeriesVertex
-
- getOutputType(int, InputType...) - Method in class org.deeplearning4j.nn.conf.graph.rnn.LastTimeStepVertex
-
- getOutputType(int, InputType...) - Method in class org.deeplearning4j.nn.conf.graph.rnn.ReverseTimeSeriesVertex
-
- getOutputType(int, InputType...) - Method in class org.deeplearning4j.nn.conf.graph.ScaleVertex
-
- getOutputType(int, InputType...) - Method in class org.deeplearning4j.nn.conf.graph.ShiftVertex
-
- getOutputType(int, InputType...) - Method in class org.deeplearning4j.nn.conf.graph.StackVertex
-
- getOutputType(int, InputType...) - Method in class org.deeplearning4j.nn.conf.graph.SubsetVertex
-
- getOutputType(int, InputType...) - Method in class org.deeplearning4j.nn.conf.graph.UnstackVertex
-
- getOutputType(InputType) - Method in interface org.deeplearning4j.nn.conf.InputPreProcessor
-
For a given type of input to this preprocessor, what is the type of the output?
- getOutputType(int, InputType) - Method in class org.deeplearning4j.nn.conf.layers.ActivationLayer
-
- getOutputType(int, InputType) - Method in class org.deeplearning4j.nn.conf.layers.BaseRecurrentLayer
-
- getOutputType(int, InputType) - Method in class org.deeplearning4j.nn.conf.layers.BatchNormalization
-
- getOutputType(int, InputType) - Method in class org.deeplearning4j.nn.conf.layers.CnnLossLayer
-
- getOutputType(int, InputType) - Method in class org.deeplearning4j.nn.conf.layers.Convolution1DLayer
-
- getOutputType(int, InputType) - Method in class org.deeplearning4j.nn.conf.layers.Convolution3D
-
- getOutputType(int, InputType) - Method in class org.deeplearning4j.nn.conf.layers.convolutional.Cropping1D
-
- getOutputType(int, InputType) - Method in class org.deeplearning4j.nn.conf.layers.convolutional.Cropping2D
-
- getOutputType(int, InputType) - Method in class org.deeplearning4j.nn.conf.layers.convolutional.Cropping3D
-
- getOutputType(int, InputType) - Method in class org.deeplearning4j.nn.conf.layers.ConvolutionLayer
-
- getOutputType(int, InputType) - Method in class org.deeplearning4j.nn.conf.layers.Deconvolution2D
-
- getOutputType(int, InputType) - Method in class org.deeplearning4j.nn.conf.layers.DepthwiseConvolution2D
-
- getOutputType(int, InputType) - Method in class org.deeplearning4j.nn.conf.layers.DropoutLayer
-
- getOutputType(int, InputType) - Method in class org.deeplearning4j.nn.conf.layers.EmbeddingSequenceLayer
-
- getOutputType(int, InputType) - Method in class org.deeplearning4j.nn.conf.layers.FeedForwardLayer
-
- getOutputType(int, InputType) - Method in class org.deeplearning4j.nn.conf.layers.GlobalPoolingLayer
-
- getOutputType(int, InputType) - Method in class org.deeplearning4j.nn.conf.layers.Layer
-
For a given type of input to this layer, what is the type of the output?
- getOutputType(int, InputType) - Method in class org.deeplearning4j.nn.conf.layers.LocalResponseNormalization
-
- getOutputType(int, InputType) - Method in class org.deeplearning4j.nn.conf.layers.misc.FrozenLayer
-
- getOutputType(int, InputType) - Method in class org.deeplearning4j.nn.conf.layers.objdetect.Yolo2OutputLayer
-
- getOutputType(int, InputType) - Method in class org.deeplearning4j.nn.conf.layers.recurrent.Bidirectional
-
- getOutputType(int, InputType) - Method in class org.deeplearning4j.nn.conf.layers.recurrent.LastTimeStep
-
- getOutputType(int, InputType) - Method in class org.deeplearning4j.nn.conf.layers.RnnLossLayer
-
- getOutputType(int, InputType) - Method in class org.deeplearning4j.nn.conf.layers.RnnOutputLayer
-
- getOutputType(int, InputType) - Method in class org.deeplearning4j.nn.conf.layers.samediff.AbstractSameDiffLayer
-
- getOutputType(int, InputType) - Method in class org.deeplearning4j.nn.conf.layers.SeparableConvolution2D
-
- getOutputType(int, InputType) - Method in class org.deeplearning4j.nn.conf.layers.SpaceToBatchLayer
-
- getOutputType(int, InputType) - Method in class org.deeplearning4j.nn.conf.layers.SpaceToDepthLayer
-
- getOutputType(int, InputType) - Method in class org.deeplearning4j.nn.conf.layers.Subsampling1DLayer
-
- getOutputType(int, InputType) - Method in class org.deeplearning4j.nn.conf.layers.Subsampling3DLayer
-
- getOutputType(int, InputType) - Method in class org.deeplearning4j.nn.conf.layers.SubsamplingLayer
-
- getOutputType(int, InputType) - Method in class org.deeplearning4j.nn.conf.layers.Upsampling1D
-
- getOutputType(int, InputType) - Method in class org.deeplearning4j.nn.conf.layers.Upsampling2D
-
- getOutputType(int, InputType) - Method in class org.deeplearning4j.nn.conf.layers.Upsampling3D
-
- getOutputType(int, InputType) - Method in class org.deeplearning4j.nn.conf.layers.util.MaskLayer
-
- getOutputType(int, InputType) - Method in class org.deeplearning4j.nn.conf.layers.util.MaskZeroLayer
-
- getOutputType(int, InputType) - Method in class org.deeplearning4j.nn.conf.layers.wrapper.BaseWrapperLayer
-
- getOutputType(int, InputType) - Method in class org.deeplearning4j.nn.conf.layers.ZeroPadding1DLayer
-
- getOutputType(int, InputType) - Method in class org.deeplearning4j.nn.conf.layers.ZeroPadding3DLayer
-
- getOutputType(int, InputType) - Method in class org.deeplearning4j.nn.conf.layers.ZeroPaddingLayer
-
- getOutputType(InputType) - Method in class org.deeplearning4j.nn.conf.preprocessor.BinomialSamplingPreProcessor
-
- getOutputType(InputType) - Method in class org.deeplearning4j.nn.conf.preprocessor.Cnn3DToFeedForwardPreProcessor
-
- getOutputType(InputType) - Method in class org.deeplearning4j.nn.conf.preprocessor.CnnToFeedForwardPreProcessor
-
- getOutputType(InputType) - Method in class org.deeplearning4j.nn.conf.preprocessor.CnnToRnnPreProcessor
-
- getOutputType(InputType) - Method in class org.deeplearning4j.nn.conf.preprocessor.ComposableInputPreProcessor
-
- getOutputType(InputType) - Method in class org.deeplearning4j.nn.conf.preprocessor.FeedForwardToCnn3DPreProcessor
-
- getOutputType(InputType) - Method in class org.deeplearning4j.nn.conf.preprocessor.FeedForwardToCnnPreProcessor
-
- getOutputType(InputType) - Method in class org.deeplearning4j.nn.conf.preprocessor.FeedForwardToRnnPreProcessor
-
- getOutputType(InputType) - Method in class org.deeplearning4j.nn.conf.preprocessor.RnnToCnnPreProcessor
-
- getOutputType(InputType) - Method in class org.deeplearning4j.nn.conf.preprocessor.RnnToFeedForwardPreProcessor
-
- getOutputType(InputType) - Method in class org.deeplearning4j.nn.conf.preprocessor.UnitVarianceProcessor
-
- getOutputType(InputType) - Method in class org.deeplearning4j.nn.conf.preprocessor.ZeroMeanAndUnitVariancePreProcessor
-
- getOutputType(InputType) - Method in class org.deeplearning4j.nn.conf.preprocessor.ZeroMeanPrePreProcessor
-
- getOutputType(InputType...) - Method in class org.deeplearning4j.nn.modelimport.keras.KerasLayer
-
Get layer output type.
- getOutputType(InputType...) - Method in class org.deeplearning4j.nn.modelimport.keras.layers.advanced.activations.KerasLeakyReLU
-
Get layer output type.
- getOutputType(InputType...) - Method in class org.deeplearning4j.nn.modelimport.keras.layers.convolutional.KerasAtrousConvolution1D
-
Get layer output type.
- getOutputType(InputType...) - Method in class org.deeplearning4j.nn.modelimport.keras.layers.convolutional.KerasAtrousConvolution2D
-
Get layer output type.
- getOutputType(InputType...) - Method in class org.deeplearning4j.nn.modelimport.keras.layers.convolutional.KerasConvolution1D
-
Get layer output type.
- getOutputType(InputType...) - Method in class org.deeplearning4j.nn.modelimport.keras.layers.convolutional.KerasConvolution2D
-
Get layer output type.
- getOutputType(InputType...) - Method in class org.deeplearning4j.nn.modelimport.keras.layers.convolutional.KerasConvolution3D
-
Get layer output type.
- getOutputType(InputType...) - Method in class org.deeplearning4j.nn.modelimport.keras.layers.convolutional.KerasCropping1D
-
Get layer output type.
- getOutputType(InputType...) - Method in class org.deeplearning4j.nn.modelimport.keras.layers.convolutional.KerasCropping2D
-
Get layer output type.
- getOutputType(InputType...) - Method in class org.deeplearning4j.nn.modelimport.keras.layers.convolutional.KerasCropping3D
-
Get layer output type.
- getOutputType(InputType...) - Method in class org.deeplearning4j.nn.modelimport.keras.layers.convolutional.KerasDeconvolution2D
-
Get layer output type.
- getOutputType(InputType...) - Method in class org.deeplearning4j.nn.modelimport.keras.layers.convolutional.KerasDepthwiseConvolution2D
-
Get layer output type.
- getOutputType(InputType...) - Method in class org.deeplearning4j.nn.modelimport.keras.layers.convolutional.KerasSeparableConvolution2D
-
Get layer output type.
- getOutputType(InputType...) - Method in class org.deeplearning4j.nn.modelimport.keras.layers.convolutional.KerasSpaceToDepth
-
Get layer output type.
- getOutputType(InputType...) - Method in class org.deeplearning4j.nn.modelimport.keras.layers.convolutional.KerasUpsampling1D
-
Get layer output type.
- getOutputType(InputType...) - Method in class org.deeplearning4j.nn.modelimport.keras.layers.convolutional.KerasUpsampling2D
-
Get layer output type.
- getOutputType(InputType...) - Method in class org.deeplearning4j.nn.modelimport.keras.layers.convolutional.KerasUpsampling3D
-
Get layer output type.
- getOutputType(InputType...) - Method in class org.deeplearning4j.nn.modelimport.keras.layers.convolutional.KerasZeroPadding1D
-
Get layer output type.
- getOutputType(InputType...) - Method in class org.deeplearning4j.nn.modelimport.keras.layers.convolutional.KerasZeroPadding2D
-
Get layer output type.
- getOutputType(InputType...) - Method in class org.deeplearning4j.nn.modelimport.keras.layers.convolutional.KerasZeroPadding3D
-
Get layer output type.
- getOutputType(InputType...) - Method in class org.deeplearning4j.nn.modelimport.keras.layers.core.KerasActivation
-
Get layer output type.
- getOutputType(InputType...) - Method in class org.deeplearning4j.nn.modelimport.keras.layers.core.KerasDense
-
Get layer output type.
- getOutputType(InputType...) - Method in class org.deeplearning4j.nn.modelimport.keras.layers.core.KerasDropout
-
Get layer output type.
- getOutputType(InputType...) - Method in class org.deeplearning4j.nn.modelimport.keras.layers.core.KerasFlatten
-
Get layer output type.
- getOutputType(InputType...) - Method in class org.deeplearning4j.nn.modelimport.keras.layers.core.KerasMerge
-
Get layer output type.
- getOutputType(InputType...) - Method in class org.deeplearning4j.nn.modelimport.keras.layers.core.KerasPermute
-
Get layer output type.
- getOutputType(InputType...) - Method in class org.deeplearning4j.nn.modelimport.keras.layers.core.KerasReshape
-
Get layer output type.
- getOutputType(InputType...) - Method in class org.deeplearning4j.nn.modelimport.keras.layers.core.KerasSpatialDropout
-
Get layer output type.
- getOutputType(InputType...) - Method in class org.deeplearning4j.nn.modelimport.keras.layers.custom.KerasLRN
-
Get layer output type.
- getOutputType(InputType...) - Method in class org.deeplearning4j.nn.modelimport.keras.layers.custom.KerasPoolHelper
-
Get layer output type.
- getOutputType(InputType...) - Method in class org.deeplearning4j.nn.modelimport.keras.layers.embeddings.KerasEmbedding
-
Get layer output type.
- getOutputType(InputType...) - Method in class org.deeplearning4j.nn.modelimport.keras.layers.KerasInput
-
Get layer output type.
- getOutputType(InputType...) - Method in class org.deeplearning4j.nn.modelimport.keras.layers.KerasLoss
-
Get layer output type.
- getOutputType(InputType...) - Method in class org.deeplearning4j.nn.modelimport.keras.layers.noise.KerasAlphaDropout
-
Get layer output type.
- getOutputType(InputType...) - Method in class org.deeplearning4j.nn.modelimport.keras.layers.noise.KerasGaussianDropout
-
Get layer output type.
- getOutputType(InputType...) - Method in class org.deeplearning4j.nn.modelimport.keras.layers.noise.KerasGaussianNoise
-
Get layer output type.
- getOutputType(InputType...) - Method in class org.deeplearning4j.nn.modelimport.keras.layers.normalization.KerasBatchNormalization
-
Get layer output type.
- getOutputType(InputType...) - Method in class org.deeplearning4j.nn.modelimport.keras.layers.pooling.KerasGlobalPooling
-
Get layer output type.
- getOutputType(InputType...) - Method in class org.deeplearning4j.nn.modelimport.keras.layers.pooling.KerasPooling1D
-
Get layer output type.
- getOutputType(InputType...) - Method in class org.deeplearning4j.nn.modelimport.keras.layers.pooling.KerasPooling2D
-
Get layer output type.
- getOutputType(InputType...) - Method in class org.deeplearning4j.nn.modelimport.keras.layers.pooling.KerasPooling3D
-
Get layer output type.
- getOutputType(InputType...) - Method in class org.deeplearning4j.nn.modelimport.keras.layers.recurrent.KerasLstm
-
Get layer output type.
- getOutputType(InputType...) - Method in class org.deeplearning4j.nn.modelimport.keras.layers.recurrent.KerasSimpleRnn
-
Get layer output type.
- getOutputType(InputType...) - Method in class org.deeplearning4j.nn.modelimport.keras.layers.wrappers.KerasBidirectional
-
Get layer output type.
- getOutputType(InputType) - Method in class org.deeplearning4j.nn.modelimport.keras.preprocessors.KerasFlattenRnnPreprocessor
-
- getOutputType(InputType) - Method in class org.deeplearning4j.nn.modelimport.keras.preprocessors.PermutePreprocessor
-
- getOutputType(InputType) - Method in class org.deeplearning4j.nn.modelimport.keras.preprocessors.ReshapePreprocessor
-
- getOutputTypeCnn3DLayers(InputType, int[], int[], int[], int[], ConvolutionMode, int, int, String, Class<?>) - Static method in class org.deeplearning4j.nn.conf.layers.InputTypeUtil
-
- getOutputTypeCnnLayers(InputType, int[], int[], int[], int[], ConvolutionMode, int, int, String, Class<?>) - Static method in class org.deeplearning4j.nn.conf.layers.InputTypeUtil
-
- getOutputTypeDeconvLayer(InputType, int[], int[], int[], int[], ConvolutionMode, int, int, String, Class<?>) - Static method in class org.deeplearning4j.nn.conf.layers.InputTypeUtil
-
- getOutputVertices() - Method in class org.deeplearning4j.nn.graph.vertex.BaseGraphVertex
-
A representation of the vertices that this vertex is connected to (outputs duing forward pass)
Specifically, if outputVertices[X].getVertexIndex() = Y, and outputVertices[X].getVertexEdgeNumber() = Z
then the Xth output of this vertex is connected to the Zth input of vertex Y
- getOutputVertices() - Method in class org.deeplearning4j.nn.graph.vertex.BaseWrapperVertex
-
- getOutputVertices() - Method in interface org.deeplearning4j.nn.graph.vertex.GraphVertex
-
A representation of the vertices that this vertex is connected to (outputs duing forward pass)
Specifically, if outputVertices[X].getVertexIndex() = Y, and outputVertices[X].getVertexEdgeNumber() = Z
then the Xth output of this vertex is connected to the Zth input of vertex Y
- getOutWeights() - Method in class org.deeplearning4j.graph.models.embeddings.InMemoryGraphLookupTable
-
- getPaddingFromBorderModeConfig(Map<String, Object>, int, KerasLayerConfiguration, int) - Static method in class org.deeplearning4j.nn.modelimport.keras.layers.convolutional.KerasConvolutionUtils
-
Get (convolution) padding from Keras layer configuration.
- getPairIterator() - Method in class org.deeplearning4j.models.glove.count.CountMap
-
- getParam(String) - Method in interface org.deeplearning4j.nn.api.Model
-
Get the parameter
- getParam(String) - Method in class org.deeplearning4j.nn.graph.ComputationGraph
-
- getParam(String) - Method in class org.deeplearning4j.nn.layers.AbstractLayer
-
- getParam(String) - Method in class org.deeplearning4j.nn.layers.BaseLayer
-
- getParam(String) - Method in class org.deeplearning4j.nn.layers.convolution.SpaceToBatch
-
- getParam(String) - Method in class org.deeplearning4j.nn.layers.convolution.SpaceToDepth
-
- getParam(String) - Method in class org.deeplearning4j.nn.layers.convolution.subsampling.Subsampling3DLayer
-
- getParam(String) - Method in class org.deeplearning4j.nn.layers.convolution.subsampling.SubsamplingLayer
-
- getParam(String) - Method in class org.deeplearning4j.nn.layers.convolution.upsampling.Upsampling2D
-
- getParam(String) - Method in class org.deeplearning4j.nn.layers.convolution.upsampling.Upsampling3D
-
- getParam(String) - Method in class org.deeplearning4j.nn.layers.normalization.LocalResponseNormalization
-
- getParam(String) - Method in class org.deeplearning4j.nn.layers.recurrent.BidirectionalLayer
-
- getParam(String) - Method in class org.deeplearning4j.nn.layers.samediff.SameDiffLayer
-
- getParam(String) - Method in class org.deeplearning4j.nn.layers.variational.VariationalAutoencoder
-
- getParam(String) - Method in class org.deeplearning4j.nn.layers.wrapper.BaseWrapperLayer
-
- getParam(String) - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
-
- getParam(String) - Method in class org.deeplearning4j.plot.BarnesHutTsne
-
- getParam() - Method in class org.deeplearning4j.spark.models.embeddings.word2vec.Word2VecFuncCall
-
Deprecated.
- getParameter(Layer, String, int, int, boolean, LayerWorkspaceMgr) - Method in class org.deeplearning4j.nn.conf.weightnoise.DropConnect
-
- getParameter(Layer, String, int, int, boolean, LayerWorkspaceMgr) - Method in interface org.deeplearning4j.nn.conf.weightnoise.IWeightNoise
-
Get the parameter, after applying weight noise
- getParameter(Layer, String, int, int, boolean, LayerWorkspaceMgr) - Method in class org.deeplearning4j.nn.conf.weightnoise.WeightNoise
-
- getParameterKeys() - Method in class org.deeplearning4j.nn.conf.layers.samediff.SDLayerParams
-
- getParameters() - Method in class org.deeplearning4j.ui.weights.beans.CompactModelAndGradient
-
- getParamMagnitudes() - Method in class org.deeplearning4j.ui.weights.beans.CompactModelAndGradient
-
- getParamName(MutableDirectBuffer, int, int) - Method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder.ParamNamesDecoder
-
- getParamName(byte[], int, int) - Method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder.ParamNamesDecoder
-
- getParams(String) - Method in class org.ansj.recognition.impl.NatureRecognition
-
获取一个词语的参数
- getParams(Forest, String) - Static method in class org.ansj.recognition.impl.UserDicNatureRecognition
-
- getParams() - Method in interface org.deeplearning4j.nn.api.layers.LayerConstraint
-
- getParams() - Method in class org.deeplearning4j.nn.updater.BaseMultiLayerUpdater
-
- getParams() - Method in class org.deeplearning4j.nn.updater.graph.ComputationGraphUpdater
-
- getParams() - Method in class org.deeplearning4j.nn.updater.LayerUpdater
-
- getParams() - Method in class org.deeplearning4j.nn.updater.MultiLayerUpdater
-
- getParamShapes() - Method in class org.deeplearning4j.nn.conf.layers.samediff.SDLayerParams
-
Get the parameter shapes for all parameters
- getParamWithNoise(String, boolean, LayerWorkspaceMgr) - Method in class org.deeplearning4j.nn.layers.BaseLayer
-
Get the parameter, after applying any weight noise (such as DropConnect) if necessary.
- getParamWithNoise(String, boolean, LayerWorkspaceMgr) - Method in class org.deeplearning4j.nn.layers.variational.VariationalAutoencoder
-
- getParent() - Method in class org.deeplearning4j.clustering.kdtree.KDTree.KDNode
-
- getParent() - Method in class org.deeplearning4j.clustering.quadtree.QuadTree
-
- getParser() - Static method in class org.deeplearning4j.text.corpora.treeparser.TreeParser
-
- getPartition(Object) - Method in class org.deeplearning4j.spark.data.shuffle.IntPartitioner
-
Deprecated.
- getPartition(Object) - Method in class org.deeplearning4j.spark.impl.common.repartition.BalancedPartitioner
-
- getPartition(Object) - Method in class org.deeplearning4j.spark.impl.common.repartition.HashingBalancedPartitioner
-
- getPartOfSpeechLevel1() - Method in class com.atilika.kuromoji.ipadic.compile.DictionaryEntry
-
- getPartOfSpeechLevel1() - Method in class com.atilika.kuromoji.ipadic.Token
-
Gets the 1st level part-of-speech tag for this token (品詞細分類1)
- getPartOfSpeechLevel2() - Method in class com.atilika.kuromoji.ipadic.compile.DictionaryEntry
-
- getPartOfSpeechLevel2() - Method in class com.atilika.kuromoji.ipadic.Token
-
Gets the 2nd level part-of-speech tag for this token (品詞細分類2)
- getPartOfSpeechLevel3() - Method in class com.atilika.kuromoji.ipadic.compile.DictionaryEntry
-
- getPartOfSpeechLevel3() - Method in class com.atilika.kuromoji.ipadic.Token
-
Gets the 3rd level part-of-speech tag for this token (品詞細分類3)
- getPartOfSpeechLevel4() - Method in class com.atilika.kuromoji.ipadic.compile.DictionaryEntry
-
- getPartOfSpeechLevel4() - Method in class com.atilika.kuromoji.ipadic.Token
-
Gets the 4th level part-of-speech tag for this token (品詞細分類4)
- getPassphrase() - Method in class org.deeplearning4j.aws.ec2.provision.HostProvisioner
-
- getPassword() - Method in class org.deeplearning4j.aws.ec2.provision.HostProvisioner
-
- getPath() - Method in class org.deeplearning4j.ui.weights.beans.CompactModelAndGradient
-
- getPathCost() - Method in class com.atilika.kuromoji.viterbi.ViterbiNode
-
- getPathInnerNodes(int) - Method in interface org.deeplearning4j.graph.models.BinaryTree
-
- getPathInnerNodes(int) - Method in class org.deeplearning4j.graph.models.deepwalk.GraphHuffman
-
- getPathInnerNodes(int) - Method in interface org.deeplearning4j.models.sequencevectors.graph.huffman.BinaryTree
-
- getPathInnerNodes(int) - Method in class org.deeplearning4j.models.sequencevectors.graph.huffman.GraphHuffman
-
- getPathLabel(String) - Method in class org.deeplearning4j.datasets.rearrange.LocalUnstructuredDataFormatter
-
- getPerplexity() - Method in class org.deeplearning4j.plot.BarnesHutTsne
-
- getPersonFreqMap() - Static method in class org.ansj.util.MyStaticValue
-
名字词性对象反序列化
- getPersonFreqReader() - Static method in class org.ansj.util.MyStaticValue
-
根据词语后缀判断词性
- getPersonMap() - Method in class org.ansj.library.name.PersonAttrLibrary
-
- getPersonReader() - Static method in class org.ansj.util.MyStaticValue
-
人名词典
- getPnorm() - Method in class org.deeplearning4j.nn.conf.layers.SubsamplingLayer
-
- getPoint(String) - Method in class org.deeplearning4j.clustering.cluster.Cluster
-
Return the point with the given id
- getPoint() - Method in class org.deeplearning4j.clustering.kdtree.KDTree.KDNode
-
- getPointAtPrecision(double) - Method in class org.deeplearning4j.eval.curves.PrecisionRecallCurve
-
Get the point (index, threshold, precision, recall) at the given precision.
Specifically, return the points at the lowest threshold that has precision equal to or greater than the
requested precision.
- getPointAtRecall(double) - Method in class org.deeplearning4j.eval.curves.PrecisionRecallCurve
-
Get the point (index, threshold, precision, recall) at the given recall.
Specifically, return the points at the highest threshold that has recall equal to or greater than the
requested recall.
- getPointAtThreshold(double) - Method in class org.deeplearning4j.eval.curves.PrecisionRecallCurve
-
Get the point (index, threshold, precision, recall) at the given threshold.
Note that if the threshold is not found exactly, the next highest threshold exceeding the requested threshold
is returned
- getPointDistanceFromClusterVariance() - Method in class org.deeplearning4j.clustering.info.ClusterSetInfo
-
- getPointLocationChange() - Method in class org.deeplearning4j.clustering.info.ClusterSetInfo
-
- getPoints() - Method in class org.deeplearning4j.models.sequencevectors.sequence.SequenceElement
-
Returns Huffman tree points
- getPointsCount() - Method in class org.deeplearning4j.clustering.info.ClusterSetInfo
-
- getPointsFartherFromCenterThan(double) - Method in class org.deeplearning4j.clustering.info.ClusterInfo
-
- getPort() - Method in class org.deeplearning4j.ui.api.UIServer
-
Get the current port for the UI
- getPort() - Method in class org.deeplearning4j.ui.play.PlayUIServer
-
- getPosFeatures() - Method in class com.atilika.kuromoji.dict.GenericDictionaryEntry
-
- getPosition() - Method in class com.atilika.kuromoji.TokenBase
-
Gets the position/start index where this token is found in the input text
- getPrecision(int) - Method in class org.deeplearning4j.eval.curves.PrecisionRecallCurve
-
- getPrecisionRecallCurve() - Method in class org.deeplearning4j.eval.ROC
-
Get the precision recall curve as array.
- getPrecisionRecallCurve(int) - Method in class org.deeplearning4j.eval.ROCBinary
-
Get the Precision-Recall curve for the specified output
- getPrecisionRecallCurve(int) - Method in class org.deeplearning4j.eval.ROCMultiClass
-
Get the (one vs.
- getPredictedClass() - Method in class org.deeplearning4j.nn.layers.objdetect.DetectedObject
-
Get the index of the predicted class (based on maximum predicted probability)
- getPredictedObjects(INDArray, double) - Method in class org.deeplearning4j.nn.layers.objdetect.Yolo2OutputLayer
-
- getPredictedObjects(INDArray, INDArray, double, double) - Static method in class org.deeplearning4j.nn.layers.objdetect.YoloUtils
-
Given the network output and a detection threshold (in range 0 to 1) determine the objects detected by
the network.
Supports minibatches - the returned
DetectedObject instances have an example number index.
Note that the dimensions are grid cell units - for example, with 416x416 input, 32x downsampling by the network
(before getting to the Yolo2OutputLayer) we have 13x13 grid cells (each corresponding to 32 pixels in the input
image).
- getPredictedTotal(T) - Method in class org.deeplearning4j.eval.ConfusionMatrix
-
Computes the total number of times the class was predicted by the classifier.
- getPredictionByPredictedClass(int) - Method in class org.deeplearning4j.eval.Evaluation
-
Get a list of predictions, for all data with the specified predicted class, regardless of the actual data
class.
- getPredictionCountsEachClass() - Method in class org.deeplearning4j.eval.EvaluationCalibration
-
- getPredictionErrors() - Method in class org.deeplearning4j.eval.Evaluation
-
Get a list of prediction errors, on a per-record basis
- getPredictions(int, int) - Method in class org.deeplearning4j.eval.Evaluation
-
Get a list of predictions in the specified confusion matrix entry (i.e., for the given actua/predicted class pair)
- getPredictionsByActualClass(int) - Method in class org.deeplearning4j.eval.Evaluation
-
Get a list of predictions, for all data with the specified actual class, regardless of the predicted
class.
- getPreProcessor() - Method in class org.deeplearning4j.datasets.datavec.RecordReaderMultiDataSetIterator
-
- getPreProcessor() - Method in class org.deeplearning4j.datasets.iterator.AbstractDataSetIterator
-
- getPreProcessor() - Method in class org.deeplearning4j.datasets.iterator.AsyncDataSetIterator
-
Returns preprocessors, if defined
- getPreProcessor() - Method in class org.deeplearning4j.datasets.iterator.AsyncMultiDataSetIterator
-
- getPreProcessor() - Method in class org.deeplearning4j.datasets.iterator.AsyncShieldDataSetIterator
-
Returns preprocessors, if defined
- getPreProcessor() - Method in class org.deeplearning4j.datasets.iterator.AsyncShieldMultiDataSetIterator
-
- getPreProcessor() - Method in class org.deeplearning4j.datasets.iterator.EarlyTerminationDataSetIterator
-
- getPreProcessor() - Method in class org.deeplearning4j.datasets.iterator.EarlyTerminationMultiDataSetIterator
-
- getPreProcessor() - Method in class org.deeplearning4j.datasets.iterator.FileSplitDataSetIterator
-
- getPreProcessor() - Method in class org.deeplearning4j.datasets.iterator.impl.BenchmarkDataSetIterator
-
- getPreProcessor() - Method in class org.deeplearning4j.datasets.iterator.impl.BenchmarkMultiDataSetIterator
-
- getPreProcessor() - Method in class org.deeplearning4j.datasets.iterator.impl.MultiDataSetIteratorAdapter
-
- getPreProcessor() - Method in class org.deeplearning4j.datasets.iterator.impl.SingletonMultiDataSetIterator
-
- getPreProcessor() - Method in class org.deeplearning4j.datasets.iterator.IteratorMultiDataSetIterator
-
- getPreProcessor() - Method in class org.deeplearning4j.datasets.iterator.MultiDataSetWrapperIterator
-
- getPreProcessor() - Method in class org.deeplearning4j.datasets.iterator.parallel.BaseParallelDataSetIterator
-
- getPreProcessor() - Method in class org.deeplearning4j.datasets.iterator.WorkspacesShieldDataSetIterator
-
- getPreProcessor() - Method in class org.deeplearning4j.iterator.CnnSentenceDataSetIterator
-
- getPreProcessor() - Method in class org.deeplearning4j.nn.conf.graph.LayerVertex
-
- getPreProcessor() - Method in class org.deeplearning4j.spark.iterator.BaseDataSetIterator
-
- getPreProcessor() - Method in class org.deeplearning4j.spark.iterator.PathSparkMultiDataSetIterator
-
- getPreProcessor() - Method in class org.deeplearning4j.spark.iterator.PortableDataStreamMultiDataSetIterator
-
- getPreProcessor() - Method in class org.deeplearning4j.spark.parameterserver.iterators.VirtualDataSetIterator
-
- getPreProcessor() - Method in class org.deeplearning4j.spark.parameterserver.iterators.VirtualMultiDataSetIterator
-
- getPreProcessor() - Method in class org.deeplearning4j.text.sentenceiterator.AggregatingSentenceIterator
-
- getPreProcessor() - Method in class org.deeplearning4j.text.sentenceiterator.BaseSentenceIterator
-
- getPreProcessor() - Method in class org.deeplearning4j.text.sentenceiterator.BasicLineIterator
-
- getPreProcessor() - Method in class org.deeplearning4j.text.sentenceiterator.BasicResultSetIterator
-
- getPreProcessor() - Method in class org.deeplearning4j.text.sentenceiterator.MutipleEpochsSentenceIterator
-
- getPreProcessor() - Method in class org.deeplearning4j.text.sentenceiterator.PrefetchingSentenceIterator
-
Deprecated.
- getPreProcessor() - Method in interface org.deeplearning4j.text.sentenceiterator.SentenceIterator
-
- getPreProcessor() - Method in class org.deeplearning4j.text.sentenceiterator.StreamLineIterator
-
- getPreProcessor() - Method in class org.deeplearning4j.text.sentenceiterator.SynchronizedSentenceIterator
-
- getPreProcessorForInputType(InputType) - Method in class org.deeplearning4j.nn.conf.layers.ActivationLayer
-
- getPreProcessorForInputType(InputType) - Method in class org.deeplearning4j.nn.conf.layers.BaseRecurrentLayer
-
- getPreProcessorForInputType(InputType) - Method in class org.deeplearning4j.nn.conf.layers.BaseUpsamplingLayer
-
- getPreProcessorForInputType(InputType) - Method in class org.deeplearning4j.nn.conf.layers.BatchNormalization
-
- getPreProcessorForInputType(InputType) - Method in class org.deeplearning4j.nn.conf.layers.CnnLossLayer
-
- getPreProcessorForInputType(InputType) - Method in class org.deeplearning4j.nn.conf.layers.Convolution1DLayer
-
- getPreProcessorForInputType(InputType) - Method in class org.deeplearning4j.nn.conf.layers.Convolution3D
-
- getPreProcessorForInputType(InputType) - Method in class org.deeplearning4j.nn.conf.layers.convolutional.Cropping1D
-
- getPreProcessorForInputType(InputType) - Method in class org.deeplearning4j.nn.conf.layers.convolutional.Cropping2D
-
- getPreProcessorForInputType(InputType) - Method in class org.deeplearning4j.nn.conf.layers.convolutional.Cropping3D
-
- getPreProcessorForInputType(InputType) - Method in class org.deeplearning4j.nn.conf.layers.ConvolutionLayer
-
- getPreProcessorForInputType(InputType) - Method in class org.deeplearning4j.nn.conf.layers.DropoutLayer
-
- getPreProcessorForInputType(InputType) - Method in class org.deeplearning4j.nn.conf.layers.FeedForwardLayer
-
- getPreProcessorForInputType(InputType) - Method in class org.deeplearning4j.nn.conf.layers.GlobalPoolingLayer
-
- getPreProcessorForInputType(InputType) - Method in class org.deeplearning4j.nn.conf.layers.Layer
-
For the given type of input to this layer, what preprocessor (if any) is required?
Returns null if no preprocessor is required, otherwise returns an appropriate
InputPreProcessor
for this layer, such as a
CnnToFeedForwardPreProcessor
- getPreProcessorForInputType(InputType) - Method in class org.deeplearning4j.nn.conf.layers.LocalResponseNormalization
-
- getPreProcessorForInputType(InputType) - Method in class org.deeplearning4j.nn.conf.layers.misc.FrozenLayer
-
- getPreProcessorForInputType(InputType) - Method in class org.deeplearning4j.nn.conf.layers.objdetect.Yolo2OutputLayer
-
- getPreProcessorForInputType(InputType) - Method in class org.deeplearning4j.nn.conf.layers.recurrent.Bidirectional
-
- getPreProcessorForInputType(InputType) - Method in class org.deeplearning4j.nn.conf.layers.RnnLossLayer
-
- getPreProcessorForInputType(InputType) - Method in class org.deeplearning4j.nn.conf.layers.RnnOutputLayer
-
- getPreProcessorForInputType(InputType) - Method in class org.deeplearning4j.nn.conf.layers.samediff.AbstractSameDiffLayer
-
- getPreProcessorForInputType(InputType) - Method in class org.deeplearning4j.nn.conf.layers.samediff.BaseSameDiffLayer
-
- getPreProcessorForInputType(InputType) - Method in class org.deeplearning4j.nn.conf.layers.SpaceToBatchLayer
-
- getPreProcessorForInputType(InputType) - Method in class org.deeplearning4j.nn.conf.layers.SpaceToDepthLayer
-
- getPreProcessorForInputType(InputType) - Method in class org.deeplearning4j.nn.conf.layers.Subsampling1DLayer
-
- getPreProcessorForInputType(InputType) - Method in class org.deeplearning4j.nn.conf.layers.Subsampling3DLayer
-
- getPreProcessorForInputType(InputType) - Method in class org.deeplearning4j.nn.conf.layers.SubsamplingLayer
-
- getPreProcessorForInputType(InputType) - Method in class org.deeplearning4j.nn.conf.layers.Upsampling1D
-
- getPreProcessorForInputType(InputType) - Method in class org.deeplearning4j.nn.conf.layers.Upsampling2D
-
- getPreProcessorForInputType(InputType) - Method in class org.deeplearning4j.nn.conf.layers.Upsampling3D
-
- getPreProcessorForInputType(InputType) - Method in class org.deeplearning4j.nn.conf.layers.util.MaskLayer
-
- getPreProcessorForInputType(InputType) - Method in class org.deeplearning4j.nn.conf.layers.util.MaskZeroLayer
-
- getPreProcessorForInputType(InputType) - Method in class org.deeplearning4j.nn.conf.layers.wrapper.BaseWrapperLayer
-
- getPreProcessorForInputType(InputType) - Method in class org.deeplearning4j.nn.conf.layers.ZeroPadding1DLayer
-
- getPreProcessorForInputType(InputType) - Method in class org.deeplearning4j.nn.conf.layers.ZeroPadding3DLayer
-
- getPreProcessorForInputType(InputType) - Method in class org.deeplearning4j.nn.conf.layers.ZeroPaddingLayer
-
- getPreProcessorForInputTypeCnn3DLayers(InputType, String) - Static method in class org.deeplearning4j.nn.conf.layers.InputTypeUtil
-
- getPreProcessorForInputTypeCnnLayers(InputType, String) - Static method in class org.deeplearning4j.nn.conf.layers.InputTypeUtil
-
- getPreprocessorForInputTypeRnnLayers(InputType, String) - Static method in class org.deeplearning4j.nn.conf.layers.InputTypeUtil
-
- getProbabilityHistogram(int) - Method in class org.deeplearning4j.eval.EvaluationCalibration
-
Return a probability histogram of the specified label class index.
- getProbabilityHistogramAllClasses() - Method in class org.deeplearning4j.eval.EvaluationCalibration
-
Return a probability histogram for all predictions/classes.
- getProbabilityMatrix(INDArray, int, int) - Method in class org.deeplearning4j.nn.layers.objdetect.Yolo2OutputLayer
-
Get the probability matrix (probability of the specified class, assuming an object is present, for all x/y
positions), from the network output activations array
- getProbabilityOfSuccess() - Method in class org.deeplearning4j.nn.conf.distribution.BinomialDistribution
-
- getProbAndLabelUsed() - Method in class org.deeplearning4j.eval.ROC
-
- getPronunciation() - Method in class com.atilika.kuromoji.ipadic.compile.DictionaryEntry
-
- getPronunciation() - Method in class com.atilika.kuromoji.ipadic.Token
-
Gets the pronunciation for this token (発音)
- getRandomConnectedVertex(int, Random) - Method in interface org.deeplearning4j.graph.api.IGraph
-
Randomly sample a vertex connected to a given vertex.
- getRandomConnectedVertex(int, Random) - Method in class org.deeplearning4j.graph.graph.Graph
-
- getRandomConnectedVertex(int, Random) - Method in class org.deeplearning4j.models.sequencevectors.graph.primitives.Graph
-
- getRandomConnectedVertex(int, Random) - Method in interface org.deeplearning4j.models.sequencevectors.graph.primitives.IGraph
-
Randomly sample a vertex connected to a given vertex.
- getReader(String) - Static method in class org.ansj.dic.DicReader
-
- getReading() - Method in class com.atilika.kuromoji.ipadic.compile.DictionaryEntry
-
- getReading() - Method in class com.atilika.kuromoji.ipadic.Token
-
Gets the reading for this token (読み) in katakana script
- getRealName() - Method in class org.ansj.domain.Term
-
- getRecall(int) - Method in class org.deeplearning4j.eval.curves.PrecisionRecallCurve
-
- getRecordMetaData(Class<T>) - Method in class org.deeplearning4j.eval.meta.Prediction
-
Convenience method for getting the record meta data as a particular class (as an alternative to casting it manually).
- getRecordReader(long, int[], DataSetType, ImageTransform) - Method in class org.deeplearning4j.datasets.fetchers.SvhnDataFetcher
-
- getRecordReader(long, int[], DataSetType, ImageTransform) - Method in class org.deeplearning4j.datasets.fetchers.TinyImageNetFetcher
-
- getRecordReader(long, int[], DataSetType, ImageTransform) - Method in class org.deeplearning4j.datasets.fetchers.UciSequenceDataFetcher
-
- getRecordReader(long, DataSetType) - Method in class org.deeplearning4j.datasets.fetchers.UciSequenceDataFetcher
-
- getRecurrentDropout(KerasLayerConfiguration, Map<String, Object>) - Static method in class org.deeplearning4j.nn.modelimport.keras.layers.recurrent.KerasRnnUtils
-
Get recurrent weight dropout from Keras layer configuration.
- getReliabilityDiagram(int) - Method in class org.deeplearning4j.eval.EvaluationCalibration
-
Get the reliability diagram for the specified class
- getReportClass() - Method in class org.deeplearning4j.nn.conf.memory.LayerMemoryReport
-
- getReportClass() - Method in class org.deeplearning4j.nn.conf.memory.MemoryReport
-
- getReportClass() - Method in class org.deeplearning4j.nn.conf.memory.NetworkMemoryReport
-
- getResidualPlot(int) - Method in class org.deeplearning4j.eval.EvaluationCalibration
-
Get the residual plot, only for examples of the specified class..
- getResidualPlotAllClasses() - Method in class org.deeplearning4j.eval.EvaluationCalibration
-
Get the residual plot for all classes combined.
- getResource() - Method in class org.deeplearning4j.text.sentenceiterator.UimaSentenceIterator
-
- getResult(Graph) - Method in class org.ansj.splitWord.analysis.BaseAnalysis
-
- getResult(Graph) - Method in class org.ansj.splitWord.analysis.DicAnalysis
-
- getResult(Graph) - Method in class org.ansj.splitWord.Analysis
-
- getResult(Graph) - Method in class org.ansj.splitWord.analysis.IndexAnalysis
-
- getResult(Graph) - Method in class org.ansj.splitWord.analysis.NlpAnalysis
-
- getResult(Graph) - Method in class org.ansj.splitWord.analysis.ToAnalysis
-
- getResult(Analysis.Merger) - Method in class org.ansj.util.Graph
-
构建最优路径
- getReverseSortedPointDistancesFromCenter() - Method in class org.deeplearning4j.clustering.info.ClusterInfo
-
- getRight() - Method in class com.atilika.kuromoji.trie.PatriciaTrie.PatriciaNode
-
Returns this node's right node
- getRight() - Method in class org.deeplearning4j.clustering.kdtree.KDTree.KDNode
-
- getRightId(int) - Method in interface com.atilika.kuromoji.dict.Dictionary
-
Gets the right id of the specified word
- getRightId() - Method in class com.atilika.kuromoji.dict.DictionaryEntryBase
-
- getRightId(int) - Method in class com.atilika.kuromoji.dict.InsertedDictionary
-
- getRightId(int) - Method in class com.atilika.kuromoji.dict.TokenInfoDictionary
-
- getRightId(int) - Method in class com.atilika.kuromoji.dict.UnknownDictionary
-
- getRightId(int) - Method in class com.atilika.kuromoji.dict.UserDictionary
-
- getRightId() - Method in class com.atilika.kuromoji.viterbi.ViterbiNode
-
- getROCBinary() - Method in class org.deeplearning4j.eval.EvaluationBinary
-
- getRocCurve() - Method in class org.deeplearning4j.eval.ROC
-
Get the ROC curve, as a set of (threshold, falsePositive, truePositive) points
- getRocCurve(int) - Method in class org.deeplearning4j.eval.ROCBinary
-
Get the ROC curve for the specified output
- getRocCurve(int) - Method in class org.deeplearning4j.eval.ROCMultiClass
-
Get the (one vs.
- getRoot() - Method in class com.atilika.kuromoji.trie.PatriciaTrie
-
- getRoot() - Method in class com.atilika.kuromoji.trie.Trie
-
Returns this trie's root node
- getRootPath() - Static method in class com.atilika.kuromoji.util.KuromojiBinFilesFetcher
-
- getRouter() - Method in interface org.deeplearning4j.api.storage.StatsStorageRouterProvider
-
- getRouter() - Method in class org.deeplearning4j.spark.impl.listeners.VanillaStatsStorageRouterProvider
-
- getRouterProvider() - Method in class org.deeplearning4j.spark.impl.paramavg.ParameterAveragingTrainingMaster
-
- getRoutes() - Method in interface org.deeplearning4j.ui.api.UIModule
-
Get a list of
Route objects, that specify GET/SET etc methods, and how these should be handled.
- getRoutes() - Method in class org.deeplearning4j.ui.module.convolutional.ConvolutionalListenerModule
-
- getRoutes() - Method in class org.deeplearning4j.ui.module.defaultModule.DefaultModule
-
- getRoutes() - Method in class org.deeplearning4j.ui.module.remote.RemoteReceiverModule
-
- getRoutes() - Method in class org.deeplearning4j.ui.module.train.TrainModule
-
- getRoutes() - Method in class org.deeplearning4j.ui.module.tsne.TsneModule
-
- getRows() - Method in class org.deeplearning4j.datasets.mnist.MnistImageFile
-
Number of rows per image.
- gets(String...) - Static method in class org.ansj.library.DicLibrary
-
根据keys获取词典集合
- gets(Collection<String>) - Static method in class org.ansj.library.DicLibrary
-
根据keys获取词典集合
- getSameModeBottomRightPadding(int[], int[], int[], int[], int[]) - Static method in class org.deeplearning4j.util.ConvolutionUtils
-
Get bottom and right padding for same mode only.
- getSameModeTopLeftPadding(int[], int[], int[], int[], int[]) - Static method in class org.deeplearning4j.util.ConvolutionUtils
-
Get top and left padding for same mode only.
- getScore() - Method in class org.ansj.app.keyword.Keyword
-
- getScore() - Method in class org.ansj.domain.NewWord
-
- getScore() - Method in class org.deeplearning4j.spark.earlystopping.BaseSparkEarlyStoppingTrainer
-
- getScore() - Method in class org.deeplearning4j.spark.earlystopping.SparkEarlyStoppingGraphTrainer
-
- getScore() - Method in class org.deeplearning4j.spark.earlystopping.SparkEarlyStoppingTrainer
-
- getScore() - Method in class org.deeplearning4j.spark.impl.graph.SparkComputationGraph
-
Gets the last (average) minibatch score from calling fit.
- getScore() - Method in class org.deeplearning4j.spark.impl.multilayer.SparkDl4jMultiLayer
-
Gets the last (average) minibatch score from calling fit.
- getScore() - Method in interface org.deeplearning4j.ui.stats.api.StatsReport
-
Get the score at the current iteration
- getScore() - Method in class org.deeplearning4j.ui.weights.beans.CompactModelAndGradient
-
- getScoreCalculator() - Method in class org.deeplearning4j.earlystopping.EarlyStoppingConfiguration
-
- getScores() - Method in class org.deeplearning4j.ui.weights.beans.CompactModelAndGradient
-
- getScoreVsIter() - Method in class org.deeplearning4j.optimize.listeners.CollectScoresIterationListener
-
- getSecondPart() - Method in class org.deeplearning4j.ui.UiConnectionInfo
-
- getSecondPart(String) - Method in class org.deeplearning4j.ui.UiConnectionInfo
-
- getSentence() - Method in class org.deeplearning4j.spark.models.embeddings.word2vec.Word2VecFuncCall
-
Deprecated.
- GetSentenceCountFunction - Class in org.deeplearning4j.spark.text.functions
-
- GetSentenceCountFunction() - Constructor for class org.deeplearning4j.spark.text.functions.GetSentenceCountFunction
-
- getSentenceCountRDD() - Method in class org.deeplearning4j.spark.text.functions.TextPipeline
-
- getSentenceWordsCountRDD() - Method in class org.deeplearning4j.spark.text.functions.TextPipeline
-
- getSeparableConvolution2DLayer() - Method in class org.deeplearning4j.nn.modelimport.keras.layers.convolutional.KerasSeparableConvolution2D
-
Get DL4J SeparableConvolution2D.
- getSequenceLabel() - Method in class org.deeplearning4j.models.sequencevectors.sequence.Sequence
-
Returns label for this sequence
- getSequenceLabels() - Method in class org.deeplearning4j.models.sequencevectors.sequence.Sequence
-
Returns all labels for this sequence
- getSequencesCount() - Method in class org.deeplearning4j.models.sequencevectors.sequence.SequenceElement
-
This method returns number of documents/sequences where this element was evidenced
- getSequencesScore() - Method in class org.deeplearning4j.models.sequencevectors.SequenceVectors
-
- getSessionID() - Method in interface org.deeplearning4j.api.storage.listener.RoutingIterationListener
-
- getSessionID() - Method in interface org.deeplearning4j.api.storage.Persistable
-
Get the session id
- getSessionID() - Method in interface org.deeplearning4j.api.storage.StorageMetaData
-
Session ID for the metadata
- getSessionID() - Method in class org.deeplearning4j.ui.stats.BaseStatsListener
-
- getSessionID() - Method in class org.deeplearning4j.ui.stats.impl.SbeStatsInitializationReport
-
- getSessionID() - Method in class org.deeplearning4j.ui.stats.impl.SbeStatsReport
-
- getSessionID(MutableDirectBuffer, int, int) - Method in class org.deeplearning4j.ui.stats.sbe.StaticInfoDecoder
-
- getSessionID(byte[], int, int) - Method in class org.deeplearning4j.ui.stats.sbe.StaticInfoDecoder
-
- getSessionID(MutableDirectBuffer, int, int) - Method in class org.deeplearning4j.ui.stats.sbe.StorageMetaDataDecoder
-
- getSessionID(byte[], int, int) - Method in class org.deeplearning4j.ui.stats.sbe.StorageMetaDataDecoder
-
- getSessionID(MutableDirectBuffer, int, int) - Method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder
-
- getSessionID(byte[], int, int) - Method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder
-
- getSessionID() - Method in class org.deeplearning4j.ui.weights.ConvolutionListenerPersistable
-
- getShallowVocabCache() - Method in class org.deeplearning4j.spark.models.paragraphvectors.SparkParagraphVectors
-
- getShallowVocabCache() - Method in class org.deeplearning4j.spark.models.sequencevectors.SparkSequenceVectors
-
- getShallowVocabCache() - Method in class org.deeplearning4j.spark.models.word2vec.SparkWord2Vec
-
- getShape(boolean) - Method in class org.deeplearning4j.nn.conf.inputs.InputType
-
Returns the shape of this InputType
- getShape() - Method in class org.deeplearning4j.nn.conf.inputs.InputType
-
Returns the shape of this InputType without minibatch dimension in the returned array
- getShape(boolean) - Method in class org.deeplearning4j.nn.conf.inputs.InputType.InputTypeConvolutional
-
- getShape(boolean) - Method in class org.deeplearning4j.nn.conf.inputs.InputType.InputTypeConvolutional3D
-
- getShape(boolean) - Method in class org.deeplearning4j.nn.conf.inputs.InputType.InputTypeConvolutionalFlat
-
- getShape(boolean) - Method in class org.deeplearning4j.nn.conf.inputs.InputType.InputTypeFeedForward
-
- getShape(boolean) - Method in class org.deeplearning4j.nn.conf.inputs.InputType.InputTypeRecurrent
-
- getShape(INDArray) - Method in class org.deeplearning4j.nn.layers.normalization.BatchNormalization
-
- getShortNameForKey(String) - Method in class org.deeplearning4j.spark.api.stats.CommonSparkTrainingStats
-
- getShortNameForKey(String) - Method in interface org.deeplearning4j.spark.api.stats.SparkTrainingStats
-
Return a short (display) name for the given key.
- getShortNameForKey(String) - Method in class org.deeplearning4j.spark.impl.paramavg.stats.ParameterAveragingTrainingMasterStats
-
- getShortNameForKey(String) - Method in class org.deeplearning4j.spark.impl.paramavg.stats.ParameterAveragingTrainingWorkerStats
-
- getSimiarlityFunction() - Method in class org.deeplearning4j.plot.BarnesHutTsne
-
- getSimpleRnnLayer() - Method in class org.deeplearning4j.nn.modelimport.keras.layers.recurrent.KerasSimpleRnn
-
Get DL4J SimpleRnn layer.
- getSize() - Method in class org.deeplearning4j.clustering.quadtree.QuadTree
-
- getSize() - Method in class org.deeplearning4j.nn.layers.convolution.upsampling.Upsampling1D
-
- getSize() - Method in class org.deeplearning4j.nn.layers.convolution.upsampling.Upsampling2D
-
- getSize() - Method in class org.deeplearning4j.nn.layers.convolution.upsampling.Upsampling3D
-
- getSortedPointDistancesFromCenter() - Method in class org.deeplearning4j.clustering.info.ClusterInfo
-
- getSourceGraph() - Method in interface org.deeplearning4j.models.sequencevectors.graph.walkers.GraphWalker
-
- getSouthEast() - Method in class org.deeplearning4j.clustering.quadtree.QuadTree
-
- getSouthWest() - Method in class org.deeplearning4j.clustering.quadtree.QuadTree
-
- getSpaceToDepthLayer() - Method in class org.deeplearning4j.nn.modelimport.keras.layers.convolutional.KerasSpaceToDepth
-
Get DL4J SpaceToDepth layer.
- getSparkContext() - Method in class org.deeplearning4j.spark.impl.graph.SparkComputationGraph
-
- getSparkContext() - Method in class org.deeplearning4j.spark.impl.multilayer.SparkDl4jMultiLayer
-
- getSparkTrainingStats() - Method in class org.deeplearning4j.spark.impl.graph.SparkComputationGraph
-
- getSparkTrainingStats() - Method in class org.deeplearning4j.spark.impl.multilayer.SparkDl4jMultiLayer
-
- getSpatialDropoutLayer() - Method in class org.deeplearning4j.nn.modelimport.keras.layers.core.KerasSpatialDropout
-
Get DL4J DropoutLayer with spatial dropout.
- getSplit(VocabCache<VocabWord>) - Method in class org.deeplearning4j.spark.models.embeddings.word2vec.VocabHolder
-
- getSplitRDDs(JavaPairRDD<T, Repr>, int) - Method in class org.deeplearning4j.spark.impl.paramavg.ParameterAveragingTrainingMaster
-
- getSplitRDDs(JavaRDD<T>, int, int) - Method in class org.deeplearning4j.spark.impl.paramavg.ParameterAveragingTrainingMaster
-
- getSplitRDDs(JavaRDD<T>, int, int) - Method in class org.deeplearning4j.spark.parameterserver.training.SharedTrainingMaster
-
- getStart() - Method in class org.ansj.util.AnsjReader
-
- getStartIndex() - Method in class com.atilika.kuromoji.viterbi.ViterbiNode
-
- getStartIndexArr() - Method in class com.atilika.kuromoji.viterbi.ViterbiLattice
-
- getStartSizeArr() - Method in class com.atilika.kuromoji.viterbi.ViterbiLattice
-
- getStartTime() - Method in class org.deeplearning4j.spark.stats.BaseEventStats
-
- getStartTime() - Method in interface org.deeplearning4j.spark.stats.EventStats
-
- getStateViewArray() - Method in interface org.deeplearning4j.nn.api.Updater
-
- getStateViewArray() - Method in class org.deeplearning4j.nn.updater.BaseMultiLayerUpdater
-
- getStaticInfo(String, String, String) - Method in interface org.deeplearning4j.api.storage.StatsStorage
-
Get the static info for the given session and worker IDs, or null if no such static info has been reported
- getStaticInfo() - Method in class org.deeplearning4j.spark.impl.listeners.VanillaStatsStorageRouter
-
- getStaticInfo(String, String, String) - Method in class org.deeplearning4j.ui.storage.BaseCollectionStatsStorage
-
- getStaticInfo(String, String, String) - Method in class org.deeplearning4j.ui.storage.sqlite.J7FileStatsStorage
-
- getStatsCollectionDurationMs() - Method in interface org.deeplearning4j.ui.stats.api.StatsReport
-
Get the number of millisecons required to calculate al of the stats.
- getStatsStorageInstances() - Method in class org.deeplearning4j.ui.api.UIServer
-
- getStatsStorageInstances() - Method in class org.deeplearning4j.ui.play.PlayUIServer
-
- getStd() - Method in class org.deeplearning4j.nn.conf.distribution.LogNormalDistribution
-
- getStd() - Method in class org.deeplearning4j.nn.conf.distribution.NormalDistribution
-
- getStd() - Method in class org.deeplearning4j.nn.conf.distribution.TruncatedNormalDistribution
-
- getStdev(StatsType) - Method in interface org.deeplearning4j.ui.stats.api.StatsReport
-
Get the standard deviation values for each parameter for the given StatsType (Parameters/Updates/Activations)
- getStdev(StatsType) - Method in class org.deeplearning4j.ui.stats.impl.java.JavaStatsReport
-
- getStdev(StatsType) - Method in class org.deeplearning4j.ui.stats.impl.SbeStatsReport
-
- getStepFunction() - Method in interface org.deeplearning4j.optimize.api.ConvexOptimizer
-
This method returns StepFunction defined within this Optimizer instance
- getStepMax() - Method in class org.deeplearning4j.optimize.solvers.BackTrackLineSearch
-
- getStopWords() - Static method in class org.deeplearning4j.text.stopwords.StopWords
-
- getStorageId() - Method in class org.deeplearning4j.models.sequencevectors.sequence.SequenceElement
-
- getStorageMetaData(String, String) - Method in interface org.deeplearning4j.api.storage.StatsStorage
-
- getStorageMetaData() - Method in class org.deeplearning4j.spark.impl.listeners.VanillaStatsStorageRouter
-
- getStorageMetaData(String, String) - Method in class org.deeplearning4j.ui.storage.BaseCollectionStatsStorage
-
- getStorageMetaData(String, String) - Method in class org.deeplearning4j.ui.storage.sqlite.J7FileStatsStorage
-
- getStorageRouter() - Method in interface org.deeplearning4j.api.storage.listener.RoutingIterationListener
-
- getStorageRouter() - Method in class org.deeplearning4j.ui.stats.BaseStatsListener
-
- getStrideFromConfig(Map<String, Object>, int, KerasLayerConfiguration) - Static method in class org.deeplearning4j.nn.modelimport.keras.layers.convolutional.KerasConvolutionUtils
-
Get (convolution) stride from Keras layer configuration.
- getStringHeader(String) - Method in class org.deeplearning4j.spark.stats.BaseEventStats
-
- getStringHeader(String) - Method in interface org.deeplearning4j.spark.stats.EventStats
-
- getStringHeader(String) - Method in class org.deeplearning4j.spark.stats.ExampleCountEventStats
-
- getStringHeader(String) - Method in class org.deeplearning4j.spark.stats.PartitionCountEventStats
-
- getSubsampling1DLayer() - Method in class org.deeplearning4j.nn.modelimport.keras.layers.pooling.KerasPooling1D
-
Get DL4J Subsampling1DLayer.
- getSubsampling2DLayer() - Method in class org.deeplearning4j.nn.modelimport.keras.layers.pooling.KerasPooling2D
-
Get DL4J SubsamplingLayer.
- getSubsampling3DLayer() - Method in class org.deeplearning4j.nn.modelimport.keras.layers.pooling.KerasPooling3D
-
Get DL4J Subsampling3DLayer.
- getSubTerm() - Method in class org.ansj.domain.Term
-
- getSubTerm(Term, Term) - Static method in class org.ansj.util.TermUtil
-
从from到to生成subterm
- getSummary() - Method in class org.ansj.app.summary.pojo.Summary
-
- getSurface() - Method in class com.atilika.kuromoji.dict.DictionaryEntryBase
-
- getSurface() - Method in class com.atilika.kuromoji.TokenBase
-
Gets the surface form of this token (表層形)
- getSurface() - Method in class com.atilika.kuromoji.viterbi.ViterbiNode
-
- getSurfaces() - Method in class com.atilika.kuromoji.compile.TokenInfoDictionaryCompilerBase
-
- getSwArch() - Method in interface org.deeplearning4j.ui.stats.api.StatsInitializationReport
-
- getSwArch(MutableDirectBuffer, int, int) - Method in class org.deeplearning4j.ui.stats.sbe.StaticInfoDecoder
-
- getSwArch(byte[], int, int) - Method in class org.deeplearning4j.ui.stats.sbe.StaticInfoDecoder
-
- getSwEnvironmentInfo() - Method in interface org.deeplearning4j.ui.stats.api.StatsInitializationReport
-
- getSwHostName() - Method in interface org.deeplearning4j.ui.stats.api.StatsInitializationReport
-
- getSwHostName(MutableDirectBuffer, int, int) - Method in class org.deeplearning4j.ui.stats.sbe.StaticInfoDecoder
-
- getSwHostName(byte[], int, int) - Method in class org.deeplearning4j.ui.stats.sbe.StaticInfoDecoder
-
- getSwJvmName() - Method in interface org.deeplearning4j.ui.stats.api.StatsInitializationReport
-
- getSwJvmName(MutableDirectBuffer, int, int) - Method in class org.deeplearning4j.ui.stats.sbe.StaticInfoDecoder
-
- getSwJvmName(byte[], int, int) - Method in class org.deeplearning4j.ui.stats.sbe.StaticInfoDecoder
-
- getSwJvmSpecVersion() - Method in interface org.deeplearning4j.ui.stats.api.StatsInitializationReport
-
- getSwJvmSpecVersion(MutableDirectBuffer, int, int) - Method in class org.deeplearning4j.ui.stats.sbe.StaticInfoDecoder
-
- getSwJvmSpecVersion(byte[], int, int) - Method in class org.deeplearning4j.ui.stats.sbe.StaticInfoDecoder
-
- getSwJvmUID() - Method in interface org.deeplearning4j.ui.stats.api.StatsInitializationReport
-
- getSwJvmUID(MutableDirectBuffer, int, int) - Method in class org.deeplearning4j.ui.stats.sbe.StaticInfoDecoder
-
- getSwJvmUID(byte[], int, int) - Method in class org.deeplearning4j.ui.stats.sbe.StaticInfoDecoder
-
- getSwJvmVersion() - Method in interface org.deeplearning4j.ui.stats.api.StatsInitializationReport
-
- getSwJvmVersion(MutableDirectBuffer, int, int) - Method in class org.deeplearning4j.ui.stats.sbe.StaticInfoDecoder
-
- getSwJvmVersion(byte[], int, int) - Method in class org.deeplearning4j.ui.stats.sbe.StaticInfoDecoder
-
- getSwNd4jBackendClass() - Method in interface org.deeplearning4j.ui.stats.api.StatsInitializationReport
-
- getSwNd4jBackendClass(MutableDirectBuffer, int, int) - Method in class org.deeplearning4j.ui.stats.sbe.StaticInfoDecoder
-
- getSwNd4jBackendClass(byte[], int, int) - Method in class org.deeplearning4j.ui.stats.sbe.StaticInfoDecoder
-
- getSwNd4jDataTypeName() - Method in interface org.deeplearning4j.ui.stats.api.StatsInitializationReport
-
- getSwNd4jDataTypeName(MutableDirectBuffer, int, int) - Method in class org.deeplearning4j.ui.stats.sbe.StaticInfoDecoder
-
- getSwNd4jDataTypeName(byte[], int, int) - Method in class org.deeplearning4j.ui.stats.sbe.StaticInfoDecoder
-
- getSwOsName() - Method in interface org.deeplearning4j.ui.stats.api.StatsInitializationReport
-
- getSwOsName(MutableDirectBuffer, int, int) - Method in class org.deeplearning4j.ui.stats.sbe.StaticInfoDecoder
-
- getSwOsName(byte[], int, int) - Method in class org.deeplearning4j.ui.stats.sbe.StaticInfoDecoder
-
- getSyn0() - Method in class org.deeplearning4j.models.embeddings.inmemory.InMemoryLookupTable
-
- getSyn0Vector(Integer, VocabCache<VocabWord>) - Method in class org.deeplearning4j.spark.models.embeddings.word2vec.VocabHolder
-
- getSyn1() - Method in class org.deeplearning4j.models.embeddings.inmemory.InMemoryLookupTable
-
- getSyn1Neg() - Method in class org.deeplearning4j.models.embeddings.inmemory.InMemoryLookupTable
-
- getSyn1Vector(Integer) - Method in class org.deeplearning4j.spark.models.embeddings.word2vec.VocabHolder
-
- getSynonyms() - Method in class org.ansj.domain.Term
-
- getSystemData() - Method in class org.deeplearning4j.ui.module.train.TrainModule
-
- getTable() - Method in class org.deeplearning4j.models.embeddings.inmemory.InMemoryLookupTable
-
- getTable() - Method in class org.deeplearning4j.spark.models.embeddings.word2vec.Word2VecParam
-
Deprecated.
- getTable() - Method in class org.deeplearning4j.spark.models.embeddings.word2vec.Word2VecPerformerVoid
-
Deprecated.
- getTableId() - Method in interface org.deeplearning4j.models.embeddings.WeightLookupTable
-
Returns unique ID of this table.
- getTag() - Method in class org.ansj.app.crf.pojo.Element
-
- getTagIfOutArr(List<Element>, int) - Method in class org.ansj.app.crf.Config
-
- getTagName(int) - Static method in class org.ansj.app.crf.Config
-
- getTailBuffer() - Method in class com.atilika.kuromoji.trie.DoubleArrayTrie
-
- getTemplate() - Method in class org.ansj.app.crf.Config
-
- getTermination() - Method in class org.deeplearning4j.parallelism.EarlyStoppingParallelTrainer
-
- getTerminationCondition() - Method in interface org.deeplearning4j.clustering.strategy.ClusteringStrategy
-
- getTermNatures(String) - Method in class org.ansj.recognition.impl.NatureRecognition
-
传入一次词语获得相关的词性
- getTerms() - Method in class org.ansj.domain.Result
-
- getTest() - Method in class org.deeplearning4j.datasets.rearrange.LocalUnstructuredDataFormatter
-
- getTestFileLabelsFilename() - Method in class org.deeplearning4j.base.EmnistFetcher
-
- getTestFileLabelsFilename() - Method in class org.deeplearning4j.base.MnistFetcher
-
- getTestFileLabelsFilename_unzipped() - Method in class org.deeplearning4j.base.EmnistFetcher
-
- getTestFileLabelsFilename_unzipped() - Method in class org.deeplearning4j.base.MnistFetcher
-
- getTestFileLabelsMD5() - Method in class org.deeplearning4j.base.EmnistFetcher
-
- getTestFileLabelsMD5() - Method in class org.deeplearning4j.base.MnistFetcher
-
- getTestFileLabelsURL() - Method in class org.deeplearning4j.base.EmnistFetcher
-
- getTestFileLabelsURL() - Method in class org.deeplearning4j.base.MnistFetcher
-
- getTestFilesFilename() - Method in class org.deeplearning4j.base.EmnistFetcher
-
- getTestFilesFilename() - Method in class org.deeplearning4j.base.MnistFetcher
-
- getTestFilesFilename_unzipped() - Method in class org.deeplearning4j.base.EmnistFetcher
-
- getTestFilesFilename_unzipped() - Method in class org.deeplearning4j.base.MnistFetcher
-
- getTestFilesMD5() - Method in class org.deeplearning4j.base.EmnistFetcher
-
- getTestFilesMD5() - Method in class org.deeplearning4j.base.MnistFetcher
-
- getTestFilesURL() - Method in class org.deeplearning4j.base.EmnistFetcher
-
- getTestFilesURL() - Method in class org.deeplearning4j.base.MnistFetcher
-
- getTestIterator() - Method in class org.deeplearning4j.datasets.iterator.DataSetIteratorSplitter
-
This method returns test iterator instance
- getTestIterator() - Method in class org.deeplearning4j.datasets.iterator.MultiDataSetIteratorSplitter
-
This method returns test iterator instance
- getTheta() - Method in class org.deeplearning4j.plot.BarnesHutTsne
-
- getThreadID() - Method in class org.deeplearning4j.spark.stats.BaseEventStats
-
- getThreadID() - Method in interface org.deeplearning4j.spark.stats.EventStats
-
- getThreshold(int) - Method in class org.deeplearning4j.eval.curves.PrecisionRecallCurve
-
- getThreshold(int) - Method in class org.deeplearning4j.eval.curves.RocCurve
-
- getTimeDistributedLayerConfig(Map<String, Object>, KerasLayerConfiguration) - Static method in class org.deeplearning4j.nn.modelimport.keras.utils.KerasLayerUtils
-
Extract inner layer config from TimeDistributed configuration and merge
it into the outer config.
- getTimeStamp() - Method in interface org.deeplearning4j.api.storage.Persistable
-
Get when this was created.
- getTimeStamp() - Method in interface org.deeplearning4j.api.storage.StorageMetaData
-
Timestamp for the metadata
- getTimeStamp() - Method in class org.deeplearning4j.ui.stats.impl.SbeStatsInitializationReport
-
- getTimeStamp() - Method in class org.deeplearning4j.ui.stats.impl.SbeStatsReport
-
- getTimeStamp() - Method in class org.deeplearning4j.ui.weights.ConvolutionListenerPersistable
-
- getTitle() - Method in class org.deeplearning4j.eval.curves.BaseCurve
-
- getTitle() - Method in class org.deeplearning4j.eval.curves.BaseHistogram
-
- getTitle() - Method in class org.deeplearning4j.eval.curves.PrecisionRecallCurve
-
- getTitle() - Method in class org.deeplearning4j.eval.curves.ReliabilityDiagram
-
- getTitle() - Method in class org.deeplearning4j.eval.curves.RocCurve
-
- getTokenInfoDictionaryCompiler(String) - Method in class com.atilika.kuromoji.compile.DictionaryCompilerBase
-
- getTokenInfoDictionaryCompiler(String) - Method in class com.atilika.kuromoji.ipadic.compile.DictionaryCompiler
-
- getTokenizer() - Static method in class org.deeplearning4j.text.corpora.treeparser.TreeParser
-
- getTokenizerFactory(VectorsConfiguration) - Static method in class org.deeplearning4j.models.embeddings.loader.WordVectorSerializer
-
- getTokenizerVarMap() - Method in class org.deeplearning4j.spark.models.embeddings.word2vec.Word2Vec
-
- getTokenPreProcessor() - Method in class org.deeplearning4j.text.tokenization.tokenizerFactory.ChineseTokenizerFactory
-
- getTokenPreProcessor() - Method in class org.deeplearning4j.text.tokenization.tokenizerfactory.DefaultTokenizerFactory
-
Returns TokenPreProcessor set for this TokenizerFactory instance
- getTokenPreProcessor() - Method in class org.deeplearning4j.text.tokenization.tokenizerfactory.JapaneseTokenizerFactory
-
- getTokenPreProcessor() - Method in class org.deeplearning4j.text.tokenization.tokenizerfactory.KoreanTokenizerFactory
-
- getTokenPreProcessor() - Method in class org.deeplearning4j.text.tokenization.tokenizerfactory.NGramTokenizerFactory
-
Returns TokenPreProcessor set for this TokenizerFactory instance
- getTokenPreProcessor() - Method in class org.deeplearning4j.text.tokenization.tokenizerfactory.PosUimaTokenizerFactory
-
Returns TokenPreProcessor set for this TokenizerFactory instance
- getTokenPreProcessor() - Method in interface org.deeplearning4j.text.tokenization.tokenizerfactory.TokenizerFactory
-
Returns TokenPreProcessor set for this TokenizerFactory instance
- getTokenPreProcessor() - Method in class org.deeplearning4j.text.tokenization.tokenizerfactory.UimaTokenizerFactory
-
Returns TokenPreProcessor set for this TokenizerFactory instance
- getTokens() - Method in class org.deeplearning4j.models.word2vec.wordstore.inmemory.InMemoryLookupCache
-
Deprecated.
- getTokens() - Method in class org.deeplearning4j.nn.layers.feedforward.autoencoder.recursive.Tree
-
- getTokens() - Method in class org.deeplearning4j.text.tokenization.tokenizer.ChineseTokenizer
-
- getTokens() - Method in class org.deeplearning4j.text.tokenization.tokenizer.DefaultStreamTokenizer
-
Returns all tokens as list of Strings
- getTokens() - Method in class org.deeplearning4j.text.tokenization.tokenizer.DefaultTokenizer
-
- getTokens() - Method in class org.deeplearning4j.text.tokenization.tokenizer.JapaneseTokenizer
-
- getTokens() - Method in class org.deeplearning4j.text.tokenization.tokenizer.KoreanTokenizer
-
- getTokens() - Method in class org.deeplearning4j.text.tokenization.tokenizer.NGramTokenizer
-
- getTokens() - Method in class org.deeplearning4j.text.tokenization.tokenizer.PosUimaTokenizer
-
- getTokens() - Method in interface org.deeplearning4j.text.tokenization.tokenizer.Tokenizer
-
Returns a list of all the tokens
- getTokens() - Method in class org.deeplearning4j.text.tokenization.tokenizer.UimaTokenizer
-
- getTopLeftXY() - Method in class org.deeplearning4j.nn.layers.objdetect.DetectedObject
-
Get the top left X/Y coordinates of the detected object
- getTopNCorrectCount() - Method in class org.deeplearning4j.eval.Evaluation
-
Return the number of correct predictions according to top N value.
- getTopNTotalCount() - Method in class org.deeplearning4j.eval.Evaluation
-
Return the total number of top N evaluations.
- getTopTree(int) - Method in class org.ansj.dic.LearnTool
-
返回学习到的新词.
- getTopTree(int, Nature) - Method in class org.ansj.dic.LearnTool
-
- getTotalDataSetObjectCount(JavaRDDLike<T, Repr>) - Method in class org.deeplearning4j.spark.impl.paramavg.ParameterAveragingTrainingMaster
-
- getTotalDataSetObjectCount(JavaRDDLike<T, Repr>) - Method in class org.deeplearning4j.spark.parameterserver.training.SharedTrainingMaster
-
- getTotalExamples() - Method in interface org.deeplearning4j.ui.stats.api.StatsReport
-
Get total number of examples that have been processed since initialization
- getTotalMemoryBytes(int, MemoryUseMode, CacheMode, DataBuffer.Type) - Method in class org.deeplearning4j.nn.conf.memory.LayerMemoryReport
-
- getTotalMemoryBytes(int, MemoryUseMode, CacheMode) - Method in class org.deeplearning4j.nn.conf.memory.MemoryReport
-
Get the total memory use in bytes for the given configuration (using the current ND4J data type)
- getTotalMemoryBytes(int, MemoryUseMode, CacheMode, DataBuffer.Type) - Method in class org.deeplearning4j.nn.conf.memory.MemoryReport
-
Get the total memory use in bytes for the given configuration
- getTotalMemoryBytes(int, MemoryUseMode, CacheMode, DataBuffer.Type) - Method in class org.deeplearning4j.nn.conf.memory.NetworkMemoryReport
-
- getTotalMinibatches() - Method in interface org.deeplearning4j.ui.stats.api.StatsReport
-
Get the total number of minibatches that have been processed since initialization
- getTotalRuntimeMs() - Method in interface org.deeplearning4j.ui.stats.api.StatsReport
-
Get the total runtime since listener/model initialization
- getTotalWordCount() - Method in class org.deeplearning4j.spark.text.functions.TextPipeline
-
- getTotalWords() - Method in class org.deeplearning4j.spark.models.embeddings.word2vec.Word2VecParam
-
Deprecated.
- getTotalWords() - Method in class org.deeplearning4j.spark.models.embeddings.word2vec.Word2VecPerformerVoid
-
Deprecated.
- getTrain() - Method in class org.deeplearning4j.datasets.rearrange.LocalUnstructuredDataFormatter
-
- getTrainingDriver() - Method in class org.deeplearning4j.spark.models.sequencevectors.learning.elements.SparkCBOW
-
- getTrainingDriver() - Method in class org.deeplearning4j.spark.models.sequencevectors.learning.elements.SparkSkipGram
-
- getTrainingDriver() - Method in class org.deeplearning4j.spark.models.sequencevectors.learning.sequence.SparkDBOW
-
- getTrainingDriver() - Method in class org.deeplearning4j.spark.models.sequencevectors.learning.sequence.SparkDM
-
- getTrainingDriver() - Method in interface org.deeplearning4j.spark.models.sequencevectors.learning.SparkElementsLearningAlgorithm
-
- getTrainingFileLabelsFilename() - Method in class org.deeplearning4j.base.EmnistFetcher
-
- getTrainingFileLabelsFilename() - Method in class org.deeplearning4j.base.MnistFetcher
-
- getTrainingFileLabelsFilename_unzipped() - Method in class org.deeplearning4j.base.EmnistFetcher
-
- getTrainingFileLabelsFilename_unzipped() - Method in class org.deeplearning4j.base.MnistFetcher
-
- getTrainingFileLabelsMD5() - Method in class org.deeplearning4j.base.EmnistFetcher
-
- getTrainingFileLabelsMD5() - Method in class org.deeplearning4j.base.MnistFetcher
-
- getTrainingFileLabelsURL() - Method in class org.deeplearning4j.base.EmnistFetcher
-
- getTrainingFileLabelsURL() - Method in class org.deeplearning4j.base.MnistFetcher
-
- getTrainingFilesFilename() - Method in class org.deeplearning4j.base.EmnistFetcher
-
- getTrainingFilesFilename() - Method in class org.deeplearning4j.base.MnistFetcher
-
- getTrainingFilesFilename_unzipped() - Method in class org.deeplearning4j.base.EmnistFetcher
-
- getTrainingFilesFilename_unzipped() - Method in class org.deeplearning4j.base.MnistFetcher
-
- getTrainingFilesMD5() - Method in class org.deeplearning4j.base.EmnistFetcher
-
- getTrainingFilesMD5() - Method in class org.deeplearning4j.base.MnistFetcher
-
- getTrainingFilesURL() - Method in class org.deeplearning4j.base.EmnistFetcher
-
- getTrainingFilesURL() - Method in class org.deeplearning4j.base.MnistFetcher
-
- getTrainingListeners() - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
-
- getTrainingMaster() - Method in class org.deeplearning4j.spark.impl.graph.SparkComputationGraph
-
- getTrainingMaster() - Method in class org.deeplearning4j.spark.impl.multilayer.SparkDl4jMultiLayer
-
- getTrainingStats() - Method in interface org.deeplearning4j.spark.api.TrainingMaster
-
Return the training statistics.
- getTrainingStats() - Method in class org.deeplearning4j.spark.impl.paramavg.ParameterAveragingTrainingMaster
-
- getTrainingStats() - Method in class org.deeplearning4j.spark.parameterserver.training.SharedTrainingMaster
-
- getTrainIterator() - Method in class org.deeplearning4j.datasets.iterator.DataSetIteratorSplitter
-
This method returns train iterator instance
- getTrainIterator() - Method in class org.deeplearning4j.datasets.iterator.MultiDataSetIteratorSplitter
-
This method returns train iterator instance
- getTree() - Method in class org.deeplearning4j.graph.models.embeddings.InMemoryGraphLookupTable
-
- getTreebankTrees(String) - Method in class org.deeplearning4j.text.corpora.treeparser.TreeParser
-
Gets trees from text.
- getTrees(String, SentencePreProcessor) - Method in class org.deeplearning4j.text.corpora.treeparser.TreeParser
-
Gets trees from text.
- getTrees(String) - Method in class org.deeplearning4j.text.corpora.treeparser.TreeParser
-
Gets trees from text.
- getTrees(String) - Method in class org.deeplearning4j.text.corpora.treeparser.TreeVectorizer
-
Vectorizes the passed in sentences
- getTreesWithLabels(String, String, List<String>) - Method in class org.deeplearning4j.text.corpora.treeparser.TreeParser
-
Gets trees from text.
- getTreesWithLabels(String, List<String>) - Method in class org.deeplearning4j.text.corpora.treeparser.TreeParser
-
Gets trees from text.
- getTreesWithLabels(String, String, List<String>) - Method in class org.deeplearning4j.text.corpora.treeparser.TreeVectorizer
-
Vectorizes the passed in sentences
- getTreesWithLabels(String, List<String>) - Method in class org.deeplearning4j.text.corpora.treeparser.TreeVectorizer
-
Vectorizes the passed in sentences
- getTruePositiveRate(int) - Method in class org.deeplearning4j.eval.curves.RocCurve
-
- getTruncatedBptt() - Method in class org.deeplearning4j.nn.modelimport.keras.layers.KerasInput
-
Returns value of truncated BPTT, if any found.
- getTwoNatureFreq(Nature, Nature) - Static method in class org.ansj.library.NatureLibrary
-
获得两个词性之间的频率
- getTwoTermFreq(Term, Term) - Static method in class org.ansj.library.NatureLibrary
-
获得两个term之间的频率
- getTwoWordFreq(Term, Term) - Static method in class org.ansj.library.NgramLibrary
-
查找两个词与词之间的频率
- getType() - Method in class com.atilika.kuromoji.viterbi.ViterbiNode
-
- getType() - Method in interface org.deeplearning4j.clustering.strategy.ClusteringStrategy
-
- getType() - Method in class org.deeplearning4j.nn.conf.inputs.InputType
-
- getType() - Method in class org.deeplearning4j.nn.conf.inputs.InputType.InputTypeConvolutional
-
- getType() - Method in class org.deeplearning4j.nn.conf.inputs.InputType.InputTypeConvolutional3D
-
- getType() - Method in class org.deeplearning4j.nn.conf.inputs.InputType.InputTypeConvolutionalFlat
-
- getType() - Method in class org.deeplearning4j.nn.conf.inputs.InputType.InputTypeFeedForward
-
- getType() - Method in class org.deeplearning4j.nn.conf.inputs.InputType.InputTypeRecurrent
-
- getType() - Method in class org.deeplearning4j.nn.layers.feedforward.autoencoder.recursive.Tree
-
The type of node; mainly extra meta data
- getTypeID() - Method in interface org.deeplearning4j.api.storage.Persistable
-
Get the type id
- getTypeID() - Method in interface org.deeplearning4j.api.storage.StorageMetaData
-
Type ID for the metadata
- getTypeID() - Method in class org.deeplearning4j.ui.stats.impl.SbeStatsInitializationReport
-
- getTypeID() - Method in class org.deeplearning4j.ui.stats.impl.SbeStatsReport
-
- getTypeID(MutableDirectBuffer, int, int) - Method in class org.deeplearning4j.ui.stats.sbe.StaticInfoDecoder
-
- getTypeID(byte[], int, int) - Method in class org.deeplearning4j.ui.stats.sbe.StaticInfoDecoder
-
- getTypeID(MutableDirectBuffer, int, int) - Method in class org.deeplearning4j.ui.stats.sbe.StorageMetaDataDecoder
-
- getTypeID(byte[], int, int) - Method in class org.deeplearning4j.ui.stats.sbe.StorageMetaDataDecoder
-
- getTypeID(MutableDirectBuffer, int, int) - Method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder
-
- getTypeID(byte[], int, int) - Method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder
-
- getTypeID() - Method in class org.deeplearning4j.ui.weights.ConvolutionListenerPersistable
-
- getUimaResource() - Method in class org.deeplearning4j.text.tokenization.tokenizerfactory.UimaTokenizerFactory
-
- getUnderlying() - Method in class org.deeplearning4j.nn.conf.layers.recurrent.LastTimeStep
-
- getUnderlyingRecurrentLayer() - Method in class org.deeplearning4j.nn.modelimport.keras.layers.wrappers.KerasBidirectional
-
Return the underlying recurrent layer of this bidirectional layer
- getUnflattenedType() - Method in class org.deeplearning4j.nn.conf.inputs.InputType.InputTypeConvolutionalFlat
-
- getUNK() - Method in interface org.deeplearning4j.models.embeddings.wordvectors.WordVectors
-
- getUNK() - Method in class org.deeplearning4j.models.sequencevectors.SequenceVectors
-
- getUNK() - Method in class org.deeplearning4j.models.word2vec.StaticWord2Vec
-
- getUnroll() - Method in class org.deeplearning4j.nn.modelimport.keras.layers.recurrent.KerasLstm
-
Get whether LSTM layer should be unrolled (for truncated BPTT).
- getUnroll() - Method in class org.deeplearning4j.nn.modelimport.keras.layers.recurrent.KerasSimpleRnn
-
Get whether SimpleRnn layer should be unrolled (for truncated BPTT).
- getUnrollRecurrentLayer(KerasLayerConfiguration, Map<String, Object>) - Static method in class org.deeplearning4j.nn.modelimport.keras.layers.recurrent.KerasRnnUtils
-
Get unroll parameter to decide whether to unroll RNN with BPTT or not.
- getUpdate(String, String, String, long) - Method in interface org.deeplearning4j.api.storage.StatsStorage
-
Get the specified update (or null, if none exists for the given session/worker ids and timestamp)
- getUpdate(String, String, String, long) - Method in class org.deeplearning4j.ui.storage.BaseCollectionStatsStorage
-
- getUpdate(String, String, String, long) - Method in class org.deeplearning4j.ui.storage.sqlite.J7FileStatsStorage
-
- getUpdateConfig() - Method in class org.deeplearning4j.ui.stats.BaseStatsListener
-
- getUpdateMagnitudes() - Method in class org.deeplearning4j.ui.weights.beans.CompactModelAndGradient
-
- getUpdateMap(String, String, String, boolean) - Method in class org.deeplearning4j.ui.storage.BaseCollectionStatsStorage
-
- getUpdateMap(String, String, String, boolean) - Method in class org.deeplearning4j.ui.storage.InMemoryStatsStorage
-
- getUpdateMap(String, String, String, boolean) - Method in class org.deeplearning4j.ui.storage.mapdb.MapDBStatsStorage
-
- getUpdater() - Method in class org.deeplearning4j.nn.graph.ComputationGraph
-
Get the ComputationGraphUpdater for the network
- getUpdater() - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
-
Get the updater for this MultiLayerNetwork
- getUpdater(Model) - Static method in class org.deeplearning4j.nn.updater.UpdaterCreator
-
- getUpdater() - Method in interface org.deeplearning4j.optimize.api.ConvexOptimizer
-
- getUpdater() - Method in class org.deeplearning4j.optimize.solvers.BaseOptimizer
-
- getUpdaterByParam(String) - Method in class org.deeplearning4j.nn.conf.layers.BaseLayer
-
Get the updater for the given parameter.
- getUpdaterByParam(String) - Method in class org.deeplearning4j.nn.conf.layers.BatchNormalization
-
- getUpdaterByParam(String) - Method in class org.deeplearning4j.nn.conf.layers.CenterLossOutputLayer
-
- getUpdaterByParam(String) - Method in class org.deeplearning4j.nn.conf.layers.Layer
-
Get the updater for the given parameter.
- getUpdaterByParam(String) - Method in class org.deeplearning4j.nn.conf.layers.misc.FrozenLayer
-
- getUpdaterByParam(String) - Method in class org.deeplearning4j.nn.conf.layers.misc.FrozenLayerWithBackprop
-
- getUpdaterByParam(String) - Method in class org.deeplearning4j.nn.conf.layers.recurrent.Bidirectional
-
Get the updater for the given parameter.
- getUpdaterByParam(String) - Method in class org.deeplearning4j.nn.conf.layers.samediff.AbstractSameDiffLayer
-
- getUpdates(String, String, String, long[]) - Method in interface org.deeplearning4j.api.storage.StatsStorage
-
Get updates for the specified times only
- getUpdates() - Method in class org.deeplearning4j.spark.impl.listeners.VanillaStatsStorageRouter
-
- getUpdates(String, String, String, long[]) - Method in class org.deeplearning4j.ui.storage.BaseCollectionStatsStorage
-
- getUpdates(String, String, String, long[]) - Method in class org.deeplearning4j.ui.storage.sqlite.J7FileStatsStorage
-
- getUpdatesBuffer() - Method in class org.deeplearning4j.spark.parameterserver.networking.SilentTrainingDriver
-
This method is viable only at Spark Workers, Master node will always have empty buffer here by design
- getUpdateTypeClass() - Method in interface org.deeplearning4j.api.storage.StorageMetaData
-
Full class name for the update information that will be posted.
- getUpdateTypeClass(MutableDirectBuffer, int, int) - Method in class org.deeplearning4j.ui.stats.sbe.StorageMetaDataDecoder
-
- getUpdateTypeClass(byte[], int, int) - Method in class org.deeplearning4j.ui.stats.sbe.StorageMetaDataDecoder
-
- getUpper(INDArray, int) - Method in class org.deeplearning4j.clustering.kdtree.HyperRect
-
- getUpper() - Method in class org.deeplearning4j.nn.conf.distribution.UniformDistribution
-
- getUpsampling1DLayer() - Method in class org.deeplearning4j.nn.modelimport.keras.layers.convolutional.KerasUpsampling1D
-
Get DL4J Upsampling1D layer.
- getUpsampling2DLayer() - Method in class org.deeplearning4j.nn.modelimport.keras.layers.convolutional.KerasUpsampling2D
-
Get DL4J Upsampling2D layer.
- getUpsampling3DLayer() - Method in class org.deeplearning4j.nn.modelimport.keras.layers.convolutional.KerasUpsampling3D
-
Get DL4J Upsampling3D layer.
- getUuid() - Method in interface org.deeplearning4j.parallelism.trainer.Trainer
-
- getV() - Method in class org.ansj.domain.KV
-
- getVaeLayer() - Method in class org.deeplearning4j.spark.impl.common.score.BaseVaeScoreWithKeyFunctionAdapter
-
- getVaeLayer() - Method in class org.deeplearning4j.spark.impl.graph.scoring.CGVaeReconstructionErrorWithKeyFunction
-
- getVaeLayer() - Method in class org.deeplearning4j.spark.impl.graph.scoring.CGVaeReconstructionProbWithKeyFunction
-
- getValue() - Method in class com.atilika.kuromoji.trie.PatriciaTrie.PatriciaNode
-
Returns this node's value
- getValue() - Method in class org.deeplearning4j.graph.api.Vertex
-
- getValue() - Method in class org.deeplearning4j.nn.conf.distribution.ConstantDistribution
-
- getValue(String) - Method in class org.deeplearning4j.spark.api.stats.CommonSparkTrainingStats
-
- getValue(String) - Method in interface org.deeplearning4j.spark.api.stats.SparkTrainingStats
-
Get the statistic value for this key
- getValue(String) - Method in class org.deeplearning4j.spark.impl.paramavg.stats.ParameterAveragingTrainingMasterStats
-
- getValue(String) - Method in class org.deeplearning4j.spark.impl.paramavg.stats.ParameterAveragingTrainingWorkerStats
-
- getVec() - Method in class org.deeplearning4j.models.word2vec.iterator.Word2VecDataFetcher
-
- getVector(int) - Method in interface org.deeplearning4j.graph.models.embeddings.GraphVectorLookupTable
-
Get the vector for the vertex with index idx
- getVector(int) - Method in class org.deeplearning4j.graph.models.embeddings.InMemoryGraphLookupTable
-
- getVectorLength() - Method in class org.deeplearning4j.spark.models.embeddings.glove.GloveParam
-
- getVectorLength() - Method in class org.deeplearning4j.spark.models.embeddings.word2vec.Word2VecParam
-
Deprecated.
- getVectorLength() - Method in class org.deeplearning4j.spark.models.embeddings.word2vec.Word2VecPerformerVoid
-
Deprecated.
- getVectorSize() - Method in class org.deeplearning4j.graph.models.deepwalk.DeepWalk
-
- getVectorSize() - Method in class org.deeplearning4j.graph.models.embeddings.GraphVectorsImpl
-
- getVectorSize() - Method in interface org.deeplearning4j.graph.models.GraphVectors
-
- getVertex(int) - Method in interface org.deeplearning4j.graph.api.IGraph
-
Get a vertex in the graph for a given index
- getVertex(int) - Method in class org.deeplearning4j.graph.graph.Graph
-
- getVertex(int) - Method in class org.deeplearning4j.models.sequencevectors.graph.primitives.Graph
-
- getVertex(int) - Method in interface org.deeplearning4j.models.sequencevectors.graph.primitives.IGraph
-
Get a vertex in the graph for a given index
- getVertex(String) - Method in class org.deeplearning4j.nn.graph.ComputationGraph
-
Return a given GraphVertex by name, or null if no vertex with that name exists
- getVertex() - Method in class org.deeplearning4j.nn.modelimport.keras.KerasLayer
-
Gets corresponding DL4J Vertex, if any.
- getVertexDegree(int) - Method in interface org.deeplearning4j.graph.api.IGraph
-
Returns the degree of the vertex.
For undirected graphs, this is just the degree.
For directed graphs, this returns the outdegree
- getVertexDegree(int) - Method in class org.deeplearning4j.graph.graph.Graph
-
- getVertexDegree(int) - Method in class org.deeplearning4j.models.sequencevectors.graph.primitives.Graph
-
- getVertexDegree(int) - Method in interface org.deeplearning4j.models.sequencevectors.graph.primitives.IGraph
-
Returns the degree of the vertex.
For undirected graphs, this is just the degree.
For directed graphs, this returns the outdegree
- getVertexEdgeNumber() - Method in class org.deeplearning4j.nn.graph.vertex.VertexIndices
-
The edge number.
- getVertexIndex() - Method in class org.deeplearning4j.nn.graph.vertex.BaseGraphVertex
-
- getVertexIndex() - Method in class org.deeplearning4j.nn.graph.vertex.BaseWrapperVertex
-
- getVertexIndex() - Method in interface org.deeplearning4j.nn.graph.vertex.GraphVertex
-
Get the index of the GraphVertex
- getVertexIndex() - Method in class org.deeplearning4j.nn.graph.vertex.VertexIndices
-
Index of the vertex
- getVertexName() - Method in class org.deeplearning4j.nn.graph.vertex.BaseGraphVertex
-
- getVertexName() - Method in class org.deeplearning4j.nn.graph.vertex.BaseWrapperVertex
-
- getVertexName() - Method in interface org.deeplearning4j.nn.graph.vertex.GraphVertex
-
Get the name/label of the GraphVertex
- getVertexVector(Vertex<V>) - Method in class org.deeplearning4j.graph.models.embeddings.GraphVectorsImpl
-
- getVertexVector(int) - Method in class org.deeplearning4j.graph.models.embeddings.GraphVectorsImpl
-
- getVertexVector(Vertex<V>) - Method in interface org.deeplearning4j.graph.models.GraphVectors
-
- getVertexVector(int) - Method in interface org.deeplearning4j.graph.models.GraphVectors
-
- getVertexVectors() - Method in class org.deeplearning4j.graph.models.embeddings.InMemoryGraphLookupTable
-
- getVertices(int[]) - Method in interface org.deeplearning4j.graph.api.IGraph
-
Get multiple vertices in the graph
- getVertices(int, int) - Method in interface org.deeplearning4j.graph.api.IGraph
-
Get multiple vertices in the graph, with secified indices
- getVertices(int[]) - Method in class org.deeplearning4j.graph.graph.Graph
-
- getVertices(int, int) - Method in class org.deeplearning4j.graph.graph.Graph
-
- getVertices(int[]) - Method in class org.deeplearning4j.models.sequencevectors.graph.primitives.Graph
-
- getVertices(int, int) - Method in class org.deeplearning4j.models.sequencevectors.graph.primitives.Graph
-
- getVertices(int[]) - Method in interface org.deeplearning4j.models.sequencevectors.graph.primitives.IGraph
-
Get multiple vertices in the graph
- getVertices(int, int) - Method in interface org.deeplearning4j.models.sequencevectors.graph.primitives.IGraph
-
Get multiple vertices in the graph, with secified indices
- getVertices() - Method in class org.deeplearning4j.nn.graph.ComputationGraph
-
Returns an array of all GraphVertex objects.
- getVocab() - Method in class org.deeplearning4j.models.embeddings.inmemory.InMemoryLookupTable
-
- getVocabCache() - Method in interface org.deeplearning4j.bagofwords.vectorizer.TextVectorizer
-
The vocab sorted in descending order
- getVocabCache() - Method in class org.deeplearning4j.models.embeddings.inmemory.InMemoryLookupTable
-
- getVocabCache() - Method in interface org.deeplearning4j.models.embeddings.WeightLookupTable
-
Returns corresponding vocabulary
- getVocabCache() - Method in class org.deeplearning4j.spark.text.functions.TextPipeline
-
- getVocabs() - Method in class org.deeplearning4j.models.word2vec.wordstore.inmemory.InMemoryLookupCache
-
Deprecated.
- getVocabulary() - Method in class org.deeplearning4j.models.word2vec.wordstore.VocabularyHolder
-
- getVocabularyWordByIdx(Integer) - Method in class org.deeplearning4j.models.word2vec.wordstore.VocabularyHolder
-
- getVocabularyWordByString(String) - Method in class org.deeplearning4j.models.word2vec.wordstore.VocabularyHolder
-
- getVocabWordListRDD() - Method in class org.deeplearning4j.spark.text.functions.TextPipeline
-
- getW1() - Method in class org.deeplearning4j.spark.models.embeddings.glove.GloveChange
-
- getW1BiasHistory() - Method in class org.deeplearning4j.spark.models.embeddings.glove.GloveChange
-
- getW1BiasUpdate() - Method in class org.deeplearning4j.spark.models.embeddings.glove.GloveChange
-
- getW1History() - Method in class org.deeplearning4j.spark.models.embeddings.glove.GloveChange
-
- getW1Update() - Method in class org.deeplearning4j.spark.models.embeddings.glove.GloveChange
-
- getW2() - Method in class org.deeplearning4j.spark.models.embeddings.glove.GloveChange
-
- getW2BiasHistory() - Method in class org.deeplearning4j.spark.models.embeddings.glove.GloveChange
-
- getW2BiasUpdate() - Method in class org.deeplearning4j.spark.models.embeddings.glove.GloveChange
-
- getW2History() - Method in class org.deeplearning4j.spark.models.embeddings.glove.GloveChange
-
- getW2Update() - Method in class org.deeplearning4j.spark.models.embeddings.glove.GloveChange
-
- getWeightAdaGrad() - Method in class org.deeplearning4j.models.glove.GloveWeightLookupTable
-
Deprecated.
- getWeightInitFromConfig(Map<String, Object>, String, boolean, KerasLayerConfiguration, int) - Static method in class org.deeplearning4j.nn.modelimport.keras.utils.KerasInitilizationUtils
-
Get weight initialization from Keras layer configuration.
- getWeightParameterKeys() - Method in class org.deeplearning4j.nn.conf.layers.samediff.SDLayerParams
-
- getWeightRegularizerFromConfig(Map<String, Object>, KerasLayerConfiguration, String, String) - Static method in class org.deeplearning4j.nn.modelimport.keras.utils.KerasRegularizerUtils
-
Get weight regularization from Keras weight regularization configuration.
- getWeights() - Method in class org.deeplearning4j.models.embeddings.inmemory.InMemoryLookupTable
-
- getWeights() - Method in interface org.deeplearning4j.models.embeddings.WeightLookupTable
-
- getWeights() - Method in class org.deeplearning4j.nn.modelimport.keras.KerasLayer
-
- getWeights() - Method in class org.deeplearning4j.spark.models.embeddings.word2vec.Word2VecParam
-
Deprecated.
- getWeights() - Method in class org.deeplearning4j.spark.models.embeddings.word2vec.Word2VecPerformerVoid
-
Deprecated.
- getWindow() - Method in class org.deeplearning4j.spark.models.embeddings.word2vec.Word2VecParam
-
Deprecated.
- getWindow() - Method in class org.deeplearning4j.spark.models.embeddings.word2vec.Word2VecPerformerVoid
-
Deprecated.
- getWindowSize() - Method in class org.deeplearning4j.graph.models.deepwalk.DeepWalk
-
- getWindowSize() - Method in class org.deeplearning4j.text.movingwindow.Window
-
- getWord() - Method in class org.deeplearning4j.models.word2vec.VocabWord
-
- getWord(int) - Method in class org.deeplearning4j.text.movingwindow.Window
-
- getWord() - Method in class org.deeplearning4j.ui.nearestneighbors.word2vec.NearestNeighborsQuery
-
- getWord2vecVarMap() - Method in class org.deeplearning4j.spark.models.embeddings.word2vec.Word2Vec
-
- getWordCost(int) - Method in interface com.atilika.kuromoji.dict.Dictionary
-
Gets the word cost of the specified word
- getWordCost() - Method in class com.atilika.kuromoji.dict.DictionaryEntryBase
-
- getWordCost(int) - Method in class com.atilika.kuromoji.dict.InsertedDictionary
-
- getWordCost(int) - Method in class com.atilika.kuromoji.dict.TokenInfoDictionary
-
- getWordCost(int) - Method in class com.atilika.kuromoji.dict.UnknownDictionary
-
- getWordCost(int) - Method in class com.atilika.kuromoji.dict.UserDictionary
-
- getWordCost() - Method in class com.atilika.kuromoji.viterbi.ViterbiNode
-
- getWordCount() - Method in class org.deeplearning4j.spark.models.embeddings.word2vec.Word2VecParam
-
Deprecated.
- getWordCount() - Method in class org.deeplearning4j.spark.models.embeddings.word2vec.Word2VecPerformerVoid
-
Deprecated.
- getWordFreqAcc() - Method in class org.deeplearning4j.spark.text.functions.TextPipeline
-
- getWordFrequencies() - Method in class org.deeplearning4j.models.word2vec.wordstore.inmemory.InMemoryLookupCache
-
Deprecated.
- getWordId() - Method in class com.atilika.kuromoji.dict.UserDictionary.UserDictionaryMatch
-
- getWordId() - Method in class com.atilika.kuromoji.viterbi.ViterbiNode
-
- getWordIdMap() - Method in class com.atilika.kuromoji.compile.TokenInfoDictionaryCompilerBase
-
Deprecated.
- GetWords - Interface in org.ansj.splitWord
-
- getWords() - Method in class org.deeplearning4j.text.movingwindow.Window
-
- GetWordsImpl - Class in org.ansj.splitWord.impl
-
- GetWordsImpl(String) - Constructor for class org.ansj.splitWord.impl.GetWordsImpl
-
构造方法，同时加载词典,传入词语相当于同时调用了setStr() ;
- GetWordsImpl() - Constructor for class org.ansj.splitWord.impl.GetWordsImpl
-
构造方法，同时加载词典
- getWordsSeen() - Method in class org.deeplearning4j.spark.models.embeddings.word2vec.Word2VecFuncCall
-
Deprecated.
- getWordsSeen() - Method in class org.deeplearning4j.spark.models.embeddings.word2vec.Word2VecParam
-
Deprecated.
- getWordVector(String) - Method in interface org.deeplearning4j.models.embeddings.wordvectors.WordVectors
-
Get the word vector for a given matrix
- getWordVector(String) - Method in class org.deeplearning4j.models.embeddings.wordvectors.WordVectorsImpl
-
Get the word vector for a given matrix
- getWordVector(String) - Method in class org.deeplearning4j.models.word2vec.StaticWord2Vec
-
Get the word vector for a given matrix
- getWordVectorMatrix(String) - Method in interface org.deeplearning4j.models.embeddings.wordvectors.WordVectors
-
Get the word vector for a given matrix
- getWordVectorMatrix(String) - Method in class org.deeplearning4j.models.embeddings.wordvectors.WordVectorsImpl
-
- getWordVectorMatrix(String) - Method in class org.deeplearning4j.models.sequencevectors.SequenceVectors
-
- getWordVectorMatrix(String) - Method in class org.deeplearning4j.models.word2vec.StaticWord2Vec
-
Get the word vector for a given matrix
- getWordVectorMatrixNormalized(String) - Method in interface org.deeplearning4j.models.embeddings.wordvectors.WordVectors
-
Returns the word vector divided by the norm2 of the array
- getWordVectorMatrixNormalized(String) - Method in class org.deeplearning4j.models.embeddings.wordvectors.WordVectorsImpl
-
Returns the word vector divided by the norm2 of the array
- getWordVectorMatrixNormalized(String) - Method in class org.deeplearning4j.models.word2vec.StaticWord2Vec
-
Returns the word vector divided by the norm2 of the array
- getWordVectors(Collection<String>) - Method in interface org.deeplearning4j.models.embeddings.wordvectors.WordVectors
-
This method returns 2D array, where each row represents corresponding word/label
- getWordVectors(Collection<String>) - Method in class org.deeplearning4j.models.embeddings.wordvectors.WordVectorsImpl
-
This method returns 2D array, where each row represents corresponding label
- getWordVectors(Collection<String>) - Method in class org.deeplearning4j.models.word2vec.StaticWord2Vec
-
This method returns 2D array, where each row represents corresponding word/label
- getWordVectorsMean(Collection<String>) - Method in interface org.deeplearning4j.models.embeddings.wordvectors.WordVectors
-
This method returns mean vector, built from words/labels passed in
- getWordVectorsMean(Collection<String>) - Method in class org.deeplearning4j.models.embeddings.wordvectors.WordVectorsImpl
-
This method returns mean vector, built from words/labels passed in
- getWordVectorsMean(Collection<String>) - Method in class org.deeplearning4j.models.word2vec.StaticWord2Vec
-
This method returns mean vector, built from words/labels passed in
- getWork() - Method in class org.deeplearning4j.models.word2vec.VocabWork
-
- getWorkerCounter(int) - Method in class org.deeplearning4j.parallelism.ParallelInference
-
- getWorkerID() - Method in interface org.deeplearning4j.api.storage.listener.RoutingIterationListener
-
- getWorkerID() - Method in interface org.deeplearning4j.api.storage.Persistable
-
Get the worker id
- getWorkerID() - Method in interface org.deeplearning4j.api.storage.StorageMetaData
-
Worker ID for the metadata
- getWorkerID() - Method in class org.deeplearning4j.ui.stats.BaseStatsListener
-
- getWorkerID() - Method in class org.deeplearning4j.ui.stats.impl.SbeStatsInitializationReport
-
- getWorkerID() - Method in class org.deeplearning4j.ui.stats.impl.SbeStatsReport
-
- getWorkerID(MutableDirectBuffer, int, int) - Method in class org.deeplearning4j.ui.stats.sbe.StaticInfoDecoder
-
- getWorkerID(byte[], int, int) - Method in class org.deeplearning4j.ui.stats.sbe.StaticInfoDecoder
-
- getWorkerID(MutableDirectBuffer, int, int) - Method in class org.deeplearning4j.ui.stats.sbe.StorageMetaDataDecoder
-
- getWorkerID(byte[], int, int) - Method in class org.deeplearning4j.ui.stats.sbe.StorageMetaDataDecoder
-
- getWorkerID(MutableDirectBuffer, int, int) - Method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder
-
- getWorkerID(byte[], int, int) - Method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder
-
- getWorkerID() - Method in class org.deeplearning4j.ui.weights.ConvolutionListenerPersistable
-
- getWorkerInstance(SparkDl4jMultiLayer) - Method in interface org.deeplearning4j.spark.api.TrainingMaster
-
Get the worker instance for this training master
- getWorkerInstance(SparkComputationGraph) - Method in interface org.deeplearning4j.spark.api.TrainingMaster
-
Get the worker instance for this training master
- getWorkerInstance(SparkDl4jMultiLayer) - Method in class org.deeplearning4j.spark.impl.paramavg.ParameterAveragingTrainingMaster
-
- getWorkerInstance(SparkComputationGraph) - Method in class org.deeplearning4j.spark.impl.paramavg.ParameterAveragingTrainingMaster
-
- getWorkerInstance(SparkDl4jMultiLayer) - Method in class org.deeplearning4j.spark.parameterserver.training.SharedTrainingMaster
-
- getWorkerInstance(SparkComputationGraph) - Method in class org.deeplearning4j.spark.parameterserver.training.SharedTrainingMaster
-
- getX() - Method in class org.deeplearning4j.clustering.quadtree.Cell
-
- getX() - Method in class org.deeplearning4j.eval.curves.BaseCurve
-
- getX() - Method in class org.deeplearning4j.eval.curves.PrecisionRecallCurve
-
- getX() - Method in class org.deeplearning4j.eval.curves.ReliabilityDiagram
-
- getX() - Method in class org.deeplearning4j.eval.curves.RocCurve
-
- getxMax() - Method in class org.deeplearning4j.models.glove.GloveWeightLookupTable
-
Deprecated.
- getxMax() - Method in class org.deeplearning4j.spark.models.embeddings.glove.GloveParam
-
- getY() - Method in class org.deeplearning4j.clustering.quadtree.Cell
-
- getY() - Method in class org.deeplearning4j.eval.curves.BaseCurve
-
- getY() - Method in class org.deeplearning4j.eval.curves.PrecisionRecallCurve
-
- getY() - Method in class org.deeplearning4j.eval.curves.ReliabilityDiagram
-
- getY() - Method in class org.deeplearning4j.eval.curves.RocCurve
-
- getYamlMapper() - Static method in class org.deeplearning4j.spark.impl.paramavg.BaseTrainingMaster
-
- getZeroMaskingFromConfig(Map<String, Object>, KerasLayerConfiguration) - Static method in class org.deeplearning4j.nn.modelimport.keras.utils.KerasLayerUtils
-
Get zero masking flag
- getZeroPadding1DLayer() - Method in class org.deeplearning4j.nn.modelimport.keras.layers.convolutional.KerasZeroPadding1D
-
Get DL4J ZeroPadding1DLayer.
- getZeroPadding2DLayer() - Method in class org.deeplearning4j.nn.modelimport.keras.layers.convolutional.KerasZeroPadding2D
-
Get DL4J ZeroPadding2DLayer.
- getZeroPadding3DLayer() - Method in class org.deeplearning4j.nn.modelimport.keras.layers.convolutional.KerasZeroPadding3D
-
Get DL4J ZeroPadding3DLayer.
- GLOBAL_MEAN - Static variable in class org.deeplearning4j.nn.params.BatchNormalizationParamInitializer
-
- GLOBAL_VAR - Static variable in class org.deeplearning4j.nn.params.BatchNormalizationParamInitializer
-
- globalConfiguration - Variable in class org.deeplearning4j.nn.conf.ComputationGraphConfiguration.GraphBuilder
-
- GlobalPoolingLayer - Class in org.deeplearning4j.nn.conf.layers
-
Global pooling layer - used to do pooling over time for RNNs, and 2d pooling for CNNs.
Supports the following
PoolingTypes: SUM, AVG, MAX, PNORM
Global pooling layer can also handle mask arrays when dealing with variable length inputs.
- GlobalPoolingLayer(PoolingType) - Constructor for class org.deeplearning4j.nn.conf.layers.GlobalPoolingLayer
-
- GlobalPoolingLayer - Class in org.deeplearning4j.nn.layers.pooling
-
Global pooling layer - used to do pooling over time for RNNs, and 2d pooling for CNNs.
Supports the following
PoolingTypes: SUM, AVG, MAX, PNORM
Global pooling layer can also handle mask arrays when dealing with variable length inputs.
- GlobalPoolingLayer(NeuralNetConfiguration) - Constructor for class org.deeplearning4j.nn.layers.pooling.GlobalPoolingLayer
-
- GlobalPoolingLayer.Builder - Class in org.deeplearning4j.nn.conf.layers
-
- GloVe<T extends SequenceElement> - Class in org.deeplearning4j.models.embeddings.learning.impl.elements
-
GloVe LearningAlgorithm implementation for SequenceVectors
- GloVe() - Constructor for class org.deeplearning4j.models.embeddings.learning.impl.elements.GloVe
-
- Glove - Class in org.deeplearning4j.models.glove
-
GlobalVectors standalone implementation for DL4j.
- Glove() - Constructor for class org.deeplearning4j.models.glove.Glove
-
- Glove - Class in org.deeplearning4j.spark.models.embeddings.glove
-
Spark glove
- Glove(String, boolean, int, int) - Constructor for class org.deeplearning4j.spark.models.embeddings.glove.Glove
-
- Glove(boolean, int, int) - Constructor for class org.deeplearning4j.spark.models.embeddings.glove.Glove
-
- GloVe.Builder<T extends SequenceElement> - Class in org.deeplearning4j.models.embeddings.learning.impl.elements
-
- Glove.Builder - Class in org.deeplearning4j.models.glove
-
- GloveChange - Class in org.deeplearning4j.spark.models.embeddings.glove
-
- GloveChange(VocabWord, VocabWord, INDArray, INDArray, double, double, double, INDArray, INDArray, double, double) - Constructor for class org.deeplearning4j.spark.models.embeddings.glove.GloveChange
-
- GloveParam - Class in org.deeplearning4j.spark.models.embeddings.glove
-
- GloveParam(int, boolean, double, Random, double, double, double, Broadcast<CounterMap<String, String>>) - Constructor for class org.deeplearning4j.spark.models.embeddings.glove.GloveParam
-
- GloveParam.Builder - Class in org.deeplearning4j.spark.models.embeddings.glove
-
- GlovePerformer - Class in org.deeplearning4j.spark.models.embeddings.glove
-
Base line glove performer
- GlovePerformer(GloveWeightLookupTable) - Constructor for class org.deeplearning4j.spark.models.embeddings.glove.GlovePerformer
-
- GloveWeightLookupTable<T extends SequenceElement> - Class in org.deeplearning4j.models.glove
-
Deprecated.
- GloveWeightLookupTable(VocabCache<T>, int, boolean, double, Random, double, double, double) - Constructor for class org.deeplearning4j.models.glove.GloveWeightLookupTable
-
Deprecated.
- GloveWeightLookupTable.Builder<T extends SequenceElement> - Class in org.deeplearning4j.models.glove
-
Deprecated.
- gMeasure(int) - Method in class org.deeplearning4j.eval.Evaluation
-
Calculate the G-measure for the given output
- gMeasure(EvaluationAveraging) - Method in class org.deeplearning4j.eval.Evaluation
-
Calculates the average G measure for all outputs using micro or macro averaging
- gMeasure(int) - Method in class org.deeplearning4j.eval.EvaluationBinary
-
Calculate the G-measure for the given output
- gMeasure(double, double) - Static method in class org.deeplearning4j.eval.EvaluationUtils
-
Calculate the G-measure from precision and recall
- goldLabel() - Method in class org.deeplearning4j.nn.layers.feedforward.autoencoder.recursive.Tree
-
- gr(double, double) - Static method in class org.deeplearning4j.clustering.util.MathUtils
-
Tests if a is greater than b.
- gradient() - Method in interface org.deeplearning4j.nn.api.Model
-
Get the gradient.
- gradient(INDArray, INDArray) - Method in class org.deeplearning4j.nn.conf.layers.variational.BernoulliReconstructionDistribution
-
- gradient(INDArray, INDArray) - Method in class org.deeplearning4j.nn.conf.layers.variational.CompositeReconstructionDistribution
-
- gradient(INDArray, INDArray) - Method in class org.deeplearning4j.nn.conf.layers.variational.ExponentialReconstructionDistribution
-
- gradient(INDArray, INDArray) - Method in class org.deeplearning4j.nn.conf.layers.variational.GaussianReconstructionDistribution
-
- gradient(INDArray, INDArray) - Method in class org.deeplearning4j.nn.conf.layers.variational.LossFunctionWrapper
-
- gradient(INDArray, INDArray) - Method in interface org.deeplearning4j.nn.conf.layers.variational.ReconstructionDistribution
-
Calculate the gradient of the negative log probability with respect to the preOutDistributionParams
- gradient(List<String>) - Method in class org.deeplearning4j.nn.gradient.DefaultGradient
-
- gradient() - Method in class org.deeplearning4j.nn.gradient.DefaultGradient
-
- Gradient - Interface in org.deeplearning4j.nn.gradient
-
Generic gradient
- gradient(List<String>) - Method in interface org.deeplearning4j.nn.gradient.Gradient
-
The full gradient as one flat vector
- gradient() - Method in interface org.deeplearning4j.nn.gradient.Gradient
-
The full gradient as one flat vector
- gradient - Variable in class org.deeplearning4j.nn.graph.ComputationGraph
-
- gradient() - Method in class org.deeplearning4j.nn.graph.ComputationGraph
-
- gradient() - Method in class org.deeplearning4j.nn.layers.AbstractLayer
-
- gradient - Variable in class org.deeplearning4j.nn.layers.BaseLayer
-
- gradient() - Method in class org.deeplearning4j.nn.layers.BaseLayer
-
- gradient() - Method in class org.deeplearning4j.nn.layers.BaseOutputLayer
-
Gets the gradient from one training iteration
- gradient() - Method in class org.deeplearning4j.nn.layers.convolution.SpaceToBatch
-
- gradient() - Method in class org.deeplearning4j.nn.layers.convolution.SpaceToDepth
-
- gradient() - Method in class org.deeplearning4j.nn.layers.convolution.subsampling.Subsampling3DLayer
-
- gradient() - Method in class org.deeplearning4j.nn.layers.convolution.subsampling.SubsamplingLayer
-
- gradient() - Method in class org.deeplearning4j.nn.layers.convolution.upsampling.Upsampling2D
-
- gradient() - Method in class org.deeplearning4j.nn.layers.convolution.upsampling.Upsampling3D
-
- gradient() - Method in class org.deeplearning4j.nn.layers.FrozenLayer
-
- gradient() - Method in class org.deeplearning4j.nn.layers.LossLayer
-
Gets the gradient from one training iteration
- gradient() - Method in class org.deeplearning4j.nn.layers.normalization.BatchNormalization
-
- gradient() - Method in class org.deeplearning4j.nn.layers.recurrent.BidirectionalLayer
-
- gradient() - Method in class org.deeplearning4j.nn.layers.recurrent.GravesBidirectionalLSTM
-
- gradient() - Method in class org.deeplearning4j.nn.layers.recurrent.GravesLSTM
-
- gradient() - Method in class org.deeplearning4j.nn.layers.recurrent.LSTM
-
- gradient() - Method in class org.deeplearning4j.nn.layers.training.CenterLossOutputLayer
-
Gets the gradient from one training iteration
- gradient - Variable in class org.deeplearning4j.nn.layers.variational.VariationalAutoencoder
-
- gradient() - Method in class org.deeplearning4j.nn.layers.variational.VariationalAutoencoder
-
- gradient() - Method in class org.deeplearning4j.nn.layers.wrapper.BaseWrapperLayer
-
- gradient - Variable in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
-
- gradient() - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
-
- gradient - Variable in class org.deeplearning4j.optimize.listeners.SharedGradient
-
- gradient(INDArray) - Method in class org.deeplearning4j.plot.BarnesHutTsne
-
- gradient() - Method in class org.deeplearning4j.plot.BarnesHutTsne
-
- GRADIENT_KEY - Static variable in class org.deeplearning4j.optimize.solvers.BaseOptimizer
-
- gradientAndScore() - Method in interface org.deeplearning4j.nn.api.Model
-
Get the gradient and score
- gradientAndScore() - Method in class org.deeplearning4j.nn.graph.ComputationGraph
-
- gradientAndScore() - Method in class org.deeplearning4j.nn.layers.AbstractLayer
-
- gradientAndScore() - Method in class org.deeplearning4j.nn.layers.BaseOutputLayer
-
- gradientAndScore() - Method in class org.deeplearning4j.nn.layers.FrozenLayer
-
- gradientAndScore() - Method in class org.deeplearning4j.nn.layers.LossLayer
-
- gradientAndScore() - Method in class org.deeplearning4j.nn.layers.objdetect.Yolo2OutputLayer
-
- gradientAndScore() - Method in class org.deeplearning4j.nn.layers.recurrent.BidirectionalLayer
-
- gradientAndScore() - Method in class org.deeplearning4j.nn.layers.training.CenterLossOutputLayer
-
- gradientAndScore() - Method in class org.deeplearning4j.nn.layers.variational.VariationalAutoencoder
-
- gradientAndScore() - Method in class org.deeplearning4j.nn.layers.wrapper.BaseWrapperLayer
-
- gradientAndScore() - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
-
- gradientAndScore(LayerWorkspaceMgr) - Method in interface org.deeplearning4j.optimize.api.ConvexOptimizer
-
The gradient and score for this optimizer
- gradientAndScore(LayerWorkspaceMgr) - Method in class org.deeplearning4j.optimize.solvers.BaseOptimizer
-
- gradientAndScore() - Method in class org.deeplearning4j.plot.BarnesHutTsne
-
- gradientCheck - Variable in class org.deeplearning4j.nn.conf.layers.CenterLossOutputLayer.Builder
-
- gradientCheck(boolean) - Method in class org.deeplearning4j.nn.conf.layers.CenterLossOutputLayer.Builder
-
- gradientCheck - Variable in class org.deeplearning4j.nn.conf.layers.CenterLossOutputLayer
-
- GradientCheckUtil - Class in org.deeplearning4j.gradientcheck
-
A utility for numerically checking gradients.
- gradientForVariable() - Method in class org.deeplearning4j.nn.gradient.DefaultGradient
-
- gradientForVariable() - Method in interface org.deeplearning4j.nn.gradient.Gradient
-
Gradient look up table
- GradientNormalization - Enum in org.deeplearning4j.nn.conf
-
Gradient normalization strategies.
- gradientNormalization - Variable in class org.deeplearning4j.nn.conf.layers.BaseLayer.Builder
-
- gradientNormalization(GradientNormalization) - Method in class org.deeplearning4j.nn.conf.layers.BaseLayer.Builder
-
Gradient normalization strategy.
- gradientNormalization - Variable in class org.deeplearning4j.nn.conf.layers.BaseLayer
-
- gradientNormalization - Variable in class org.deeplearning4j.nn.conf.NeuralNetConfiguration.Builder
-
- gradientNormalization(GradientNormalization) - Method in class org.deeplearning4j.nn.conf.NeuralNetConfiguration.Builder
-
Gradient normalization strategy.
- gradientNormalization(GradientNormalization) - Method in class org.deeplearning4j.nn.transferlearning.FineTuneConfiguration.Builder
-
Gradient normalization strategy.
- gradientNormalization - Variable in class org.deeplearning4j.nn.transferlearning.FineTuneConfiguration
-
- gradientNormalizationThreshold - Variable in class org.deeplearning4j.nn.conf.layers.BaseLayer.Builder
-
- gradientNormalizationThreshold(double) - Method in class org.deeplearning4j.nn.conf.layers.BaseLayer.Builder
-
Threshold for gradient normalization, only used for GradientNormalization.ClipL2PerLayer,
GradientNormalization.ClipL2PerParamType, and GradientNormalization.ClipElementWiseAbsoluteValue
Not used otherwise.
L2 threshold for first two types of clipping, or absolute value threshold for last type of clipping.
- gradientNormalizationThreshold - Variable in class org.deeplearning4j.nn.conf.layers.BaseLayer
-
- gradientNormalizationThreshold - Variable in class org.deeplearning4j.nn.conf.NeuralNetConfiguration.Builder
-
- gradientNormalizationThreshold(double) - Method in class org.deeplearning4j.nn.conf.NeuralNetConfiguration.Builder
-
Threshold for gradient normalization, only used for GradientNormalization.ClipL2PerLayer,
GradientNormalization.ClipL2PerParamType, and GradientNormalization.ClipElementWiseAbsoluteValue
Not used otherwise.
L2 threshold for first two types of clipping, or absolute value threshold for last type of clipping.
Note: values set by this method will be applied to all applicable layers in the network, unless a different
value is explicitly set on a given layer.
- gradientNormalizationThreshold(double) - Method in class org.deeplearning4j.nn.transferlearning.FineTuneConfiguration.Builder
-
Threshold for gradient normalization, only used for GradientNormalization.ClipL2PerLayer,
GradientNormalization.ClipL2PerParamType, and GradientNormalization.ClipElementWiseAbsoluteValue
Not used otherwise.
L2 threshold for first two types of clipping, or absolute value threshold for last type of clipping
- gradientNormalizationThreshold - Variable in class org.deeplearning4j.nn.transferlearning.FineTuneConfiguration
-
- gradients - Variable in class org.deeplearning4j.nn.layers.samediff.SameDiffLayer
-
- gradients - Variable in class org.deeplearning4j.optimize.solvers.accumulation.BasicGradientsAccumulator
-
- GradientsAccumulator - Interface in org.deeplearning4j.optimize.solvers.accumulation
-
- gradientsAccumulator(GradientsAccumulator) - Method in class org.deeplearning4j.parallelism.ParallelWrapper.Builder
-
This method allows you to specify GradientsAccumulator instance to be used in this ParallelWrapper instance
PLEASE NOTE: This method is applicable only to gradients sharing mechanics.
- gradientsAccumulator - Variable in class org.deeplearning4j.parallelism.ParallelWrapper
-
- gradientsFlattened - Variable in class org.deeplearning4j.nn.layers.BaseLayer
-
- gradientsFlattened - Variable in class org.deeplearning4j.nn.layers.variational.VariationalAutoencoder
-
- GradientStepFunction - Class in org.deeplearning4j.nn.conf.stepfunctions
-
Normal gradient step function
- GradientStepFunction() - Constructor for class org.deeplearning4j.nn.conf.stepfunctions.GradientStepFunction
-
- GradientStepFunction - Class in org.deeplearning4j.optimize.stepfunctions
-
Normal gradient step function
- GradientStepFunction() - Constructor for class org.deeplearning4j.optimize.stepfunctions.GradientStepFunction
-
- gradientViews - Variable in class org.deeplearning4j.nn.layers.BaseLayer
-
- gradientViews - Variable in class org.deeplearning4j.nn.layers.variational.VariationalAutoencoder
-
- Graph - Class in org.ansj.util
-
最短路径
- Graph(String) - Constructor for class org.ansj.util.Graph
-
- Graph<V,E> - Class in org.deeplearning4j.graph.graph
-
Graph, where all edges and vertices are stored in-memory.
Internally, this is a directed graph with adjacency list representation; however, if undirected edges
are added, these edges are duplicated internally to allow for fast lookup.
Depending on the value of allowMultipleEdges, this graph implementation may or may not allow
multiple edges between any two adjacent nodes.
- Graph(int, VertexFactory<V>) - Constructor for class org.deeplearning4j.graph.graph.Graph
-
- Graph(int, boolean, VertexFactory<V>) - Constructor for class org.deeplearning4j.graph.graph.Graph
-
- Graph(List<Vertex<V>>, boolean) - Constructor for class org.deeplearning4j.graph.graph.Graph
-
- Graph(List<Vertex<V>>) - Constructor for class org.deeplearning4j.graph.graph.Graph
-
- graph - Variable in class org.deeplearning4j.graph.models.embeddings.GraphVectorsImpl
-
- Graph<V extends SequenceElement,E extends Number> - Class in org.deeplearning4j.models.sequencevectors.graph.primitives
-
Graph, where all edges and vertices are stored in-memory.
Internally, this is a directed graph with adjacency list representation; however, if undirected edges
are added, these edges are duplicated internally to allow for fast lookup.
Depending on the value of allowMultipleEdges, this graph implementation may or may not allow
multiple edges between any two adjacent nodes.
- Graph(int, VertexFactory<V>) - Constructor for class org.deeplearning4j.models.sequencevectors.graph.primitives.Graph
-
- Graph(int, boolean, VertexFactory<V>) - Constructor for class org.deeplearning4j.models.sequencevectors.graph.primitives.Graph
-
- Graph(List<Vertex<V>>, boolean) - Constructor for class org.deeplearning4j.models.sequencevectors.graph.primitives.Graph
-
- Graph(Collection<V>, boolean) - Constructor for class org.deeplearning4j.models.sequencevectors.graph.primitives.Graph
-
- Graph(List<Vertex<V>>) - Constructor for class org.deeplearning4j.models.sequencevectors.graph.primitives.Graph
-
- Graph() - Constructor for class org.deeplearning4j.models.sequencevectors.graph.primitives.Graph
-
- graph - Variable in class org.deeplearning4j.nn.graph.vertex.BaseGraphVertex
-
- GraphBuilder(NeuralNetConfiguration.Builder) - Constructor for class org.deeplearning4j.nn.conf.ComputationGraphConfiguration.GraphBuilder
-
- GraphBuilder(ComputationGraphConfiguration, NeuralNetConfiguration.Builder) - Constructor for class org.deeplearning4j.nn.conf.ComputationGraphConfiguration.GraphBuilder
-
- graphBuilder() - Method in class org.deeplearning4j.nn.conf.NeuralNetConfiguration.Builder
-
Create a GraphBuilder (for creating a ComputationGraphConfiguration).
- GraphBuilder(ComputationGraph) - Constructor for class org.deeplearning4j.nn.transferlearning.TransferLearning.GraphBuilder
-
Computation Graph to tweak for transfer learning
- graphBuilder(String) - Method in class org.deeplearning4j.zoo.model.InceptionResNetV1
-
- graphBuilder() - Method in class org.deeplearning4j.zoo.model.NASNet
-
- graphBuilder() - Method in class org.deeplearning4j.zoo.model.ResNet50
-
- graphBuilder() - Method in class org.deeplearning4j.zoo.model.SqueezeNet
-
- graphBuilder() - Method in class org.deeplearning4j.zoo.model.UNet
-
- graphBuilder() - Method in class org.deeplearning4j.zoo.model.Xception
-
- GraphBuilderModule - Interface in org.deeplearning4j.nn.conf.module
-
GraphBuilderModule for nn layers.
- GraphFeedForwardWithKeyFunction<K> - Class in org.deeplearning4j.spark.impl.graph.scoring
-
Function to feed-forward examples, and get the network output (for example, class probabilities).
- GraphFeedForwardWithKeyFunction(Broadcast<INDArray>, Broadcast<String>, int) - Constructor for class org.deeplearning4j.spark.impl.graph.scoring.GraphFeedForwardWithKeyFunction
-
- GraphHuffman - Class in org.deeplearning4j.graph.models.deepwalk
-
An implementation of a Huffman tree specifically for graphs.
- GraphHuffman(int) - Constructor for class org.deeplearning4j.graph.models.deepwalk.GraphHuffman
-
- GraphHuffman(int, int) - Constructor for class org.deeplearning4j.graph.models.deepwalk.GraphHuffman
-
- GraphHuffman - Class in org.deeplearning4j.models.sequencevectors.graph.huffman
-
An implementation of a Huffman tree specifically for graphs.
- GraphHuffman(int) - Constructor for class org.deeplearning4j.models.sequencevectors.graph.huffman.GraphHuffman
-
- GraphHuffman(int, int) - Constructor for class org.deeplearning4j.models.sequencevectors.graph.huffman.GraphHuffman
-
- graphIndices - Variable in class org.deeplearning4j.nn.graph.ComputationGraph
-
Topological sort and vertex index/name + name/index mapping
- GraphIndices - Class in org.deeplearning4j.nn.graph.util
-
Simple helper class for ComputationGraph topological sort and vertex index/name + name/index mapping
- GraphIndices() - Constructor for class org.deeplearning4j.nn.graph.util.GraphIndices
-
- GraphInfo() - Constructor for class org.deeplearning4j.ui.module.train.TrainModuleUtils.GraphInfo
-
- GraphLoader - Class in org.deeplearning4j.graph.data
-
Utility methods for loading graphs
- GraphTransformer<T extends SequenceElement> - Class in org.deeplearning4j.models.sequencevectors.transformers.impl
-
This class is used to build vocabulary and sequences out of graph, via GraphWalkers
- GraphTransformer() - Constructor for class org.deeplearning4j.models.sequencevectors.transformers.impl.GraphTransformer
-
- GraphTransformer.Builder<T extends SequenceElement> - Class in org.deeplearning4j.models.sequencevectors.transformers.impl
-
- GraphVectorLookupTable - Interface in org.deeplearning4j.graph.models.embeddings
-
Lookup table for vector representations of the vertices in a graph
- GraphVectors<V,E> - Interface in org.deeplearning4j.graph.models
-
Vectors for nodes in a graph.
- GraphVectorSerializer - Class in org.deeplearning4j.graph.models.loader
-
GraphVectorSerializer: Provide static methods to save and load DeepWalk/Graph vectors
- GraphVectorsImpl<V,E> - Class in org.deeplearning4j.graph.models.embeddings
-
Base implementation for GraphVectors.
- GraphVectorsImpl() - Constructor for class org.deeplearning4j.graph.models.embeddings.GraphVectorsImpl
-
- GraphVertex - Class in org.deeplearning4j.nn.conf.graph
-
A GraphVertex is a vertex in the computation graph.
- GraphVertex() - Constructor for class org.deeplearning4j.nn.conf.graph.GraphVertex
-
- GraphVertex - Interface in org.deeplearning4j.nn.graph.vertex
-
A GraphVertex is a vertex in the computation graph.
- GraphWalker<T extends SequenceElement> - Interface in org.deeplearning4j.models.sequencevectors.graph.walkers
-
This interface describes methods needed for various DeepWalk-related implementations
- GraphWalkIterator<T> - Interface in org.deeplearning4j.graph.iterator
-
Interface/iterator representing a sequence of walks on a graph
For example, a GraphWalkIterator<T> can represesnt a set of independent random walks on a graph
- GraphWalkIteratorProvider<V> - Interface in org.deeplearning4j.graph.iterator.parallel
-
GraphWalkIteratorProvider: implementations of this interface provide a set of GraphWalkIterator objects.
- GravesBidirectionalLSTM - Class in org.deeplearning4j.nn.conf.layers
-
- GravesBidirectionalLSTM - Class in org.deeplearning4j.nn.layers.recurrent
-
RNN tutorial: http://deeplearning4j.org/usingrnns.html
READ THIS FIRST
Bdirectional LSTM layer implementation.
- GravesBidirectionalLSTM(NeuralNetConfiguration) - Constructor for class org.deeplearning4j.nn.layers.recurrent.GravesBidirectionalLSTM
-
- GravesBidirectionalLSTM(NeuralNetConfiguration, INDArray) - Constructor for class org.deeplearning4j.nn.layers.recurrent.GravesBidirectionalLSTM
-
- GravesBidirectionalLSTM.Builder - Class in org.deeplearning4j.nn.conf.layers
-
Deprecated.
- GravesBidirectionalLSTMParamInitializer - Class in org.deeplearning4j.nn.params
-
LSTM Parameter initializer, for LSTM based on
Graves: Supervised Sequence Labelling with Recurrent Neural Networks
http://www.cs.toronto.edu/~graves/phd.pdf
- GravesBidirectionalLSTMParamInitializer() - Constructor for class org.deeplearning4j.nn.params.GravesBidirectionalLSTMParamInitializer
-
- GravesLSTM - Class in org.deeplearning4j.nn.conf.layers
-
LSTM recurrent net, based on Graves: Supervised Sequence Labelling with Recurrent Neural Networks
http://www.cs.toronto.edu/~graves/phd.pdf
- GravesLSTM - Class in org.deeplearning4j.nn.layers.recurrent
-
LSTM layer implementation.
- GravesLSTM(NeuralNetConfiguration) - Constructor for class org.deeplearning4j.nn.layers.recurrent.GravesLSTM
-
- GravesLSTM(NeuralNetConfiguration, INDArray) - Constructor for class org.deeplearning4j.nn.layers.recurrent.GravesLSTM
-
- GravesLSTM.Builder - Class in org.deeplearning4j.nn.conf.layers
-
- GravesLSTMParamInitializer - Class in org.deeplearning4j.nn.params
-
LSTM Parameter initializer, for LSTM based on
Graves: Supervised Sequence Labelling with Recurrent Neural Networks
http://www.cs.toronto.edu/~graves/phd.pdf
- GravesLSTMParamInitializer() - Constructor for class org.deeplearning4j.nn.params.GravesLSTMParamInitializer
-
- GREATER - Static variable in class org.deeplearning4j.clustering.kdtree.KDTree
-
- GROUP - Static variable in class com.atilika.kuromoji.dict.CharacterDefinitions
-
- groupId - Variable in class org.deeplearning4j.streaming.routes.DL4jServeRouteBuilder
-
- GroupSizeEncodingDecoder - Class in org.deeplearning4j.ui.stats.sbe
-
- GroupSizeEncodingDecoder() - Constructor for class org.deeplearning4j.ui.stats.sbe.GroupSizeEncodingDecoder
-
- GroupSizeEncodingEncoder - Class in org.deeplearning4j.ui.stats.sbe
-
- GroupSizeEncodingEncoder() - Constructor for class org.deeplearning4j.ui.stats.sbe.GroupSizeEncodingEncoder
-
- GrowableIntArray(int) - Constructor for class com.atilika.kuromoji.compile.WordIdMapCompiler.GrowableIntArray
-
- GrowableIntArray() - Constructor for class com.atilika.kuromoji.compile.WordIdMapCompiler.GrowableIntArray
-
- gt(DataSet, DataSet) - Method in class org.deeplearning4j.spark.ordering.DataSetOrdering
-
- gteq(DataSet, DataSet) - Method in class org.deeplearning4j.spark.ordering.DataSetOrdering
-
- guessNature(String) - Static method in class org.ansj.recognition.impl.NatureRecognition
-
通过规则 猜测词性
- gunzipFile(File, File) - Static method in class org.deeplearning4j.base.MnistFetcher
-
- gz - Variable in class org.deeplearning4j.nn.layers.recurrent.FwdPassReturn
-
- i - Variable in class org.ansj.splitWord.impl.GetWordsImpl
-
- I18N - Interface in org.deeplearning4j.ui.api
-
Interface to handle user interface internationalization.
- I18NProvider - Class in org.deeplearning4j.ui.i18n
-
Returns the currently used I18N (Internationalization) class
- I18NProvider() - Constructor for class org.deeplearning4j.ui.i18n.I18NProvider
-
- I18NResource - Class in org.deeplearning4j.ui.i18n
-
- I18NResource() - Constructor for class org.deeplearning4j.ui.i18n.I18NResource
-
- I18NRoute - Class in org.deeplearning4j.ui.play.staticroutes
-
Route for global internationalization setting
- I18NRoute() - Constructor for class org.deeplearning4j.ui.play.staticroutes.I18NRoute
-
- i2d - Variable in class org.deeplearning4j.nn.layers.convolution.ConvolutionLayer
-
- ia - Variable in class org.deeplearning4j.nn.layers.recurrent.FwdPassReturn
-
- id - Variable in class org.ansj.domain.TermNatures
-
词的id
- id - Variable in class org.deeplearning4j.optimize.listeners.SharedGradient
-
- id - Variable in class org.deeplearning4j.ui.standalone.ComponentObject
-
- IDCardRecognition - Class in org.ansj.recognition.impl
-
基于规则的新词发现，身份证号码识别
- IDCardRecognition() - Constructor for class org.ansj.recognition.impl.IDCardRecognition
-
- idf(double, double) - Static method in class org.deeplearning4j.clustering.util.MathUtils
-
Inverse document frequency: the total docs divided by the number of times the word
appeared in a document
- IDropout - Interface in org.deeplearning4j.nn.conf.dropout
-
IDropout instances operate on an activations array, modifying or dropping values at training time only.
- iDropout - Variable in class org.deeplearning4j.nn.conf.layers.Layer.Builder
-
- iDropout - Variable in class org.deeplearning4j.nn.conf.layers.Layer
-
- idropOut - Variable in class org.deeplearning4j.nn.conf.NeuralNetConfiguration.Builder
-
- idxCounter - Variable in class org.deeplearning4j.models.embeddings.loader.WordVectorSerializer.BinaryReader
-
- IEarlyStoppingTrainer<T extends Model> - Interface in org.deeplearning4j.earlystopping.trainer
-
Interface for early stopping trainers
- IEvaluateAggregateFunction<T extends IEvaluation> - Class in org.deeplearning4j.spark.impl.multilayer.evaluation
-
A simple function to merge IEvaluation instances
- IEvaluateAggregateFunction() - Constructor for class org.deeplearning4j.spark.impl.multilayer.evaluation.IEvaluateAggregateFunction
-
- IEvaluateFlatMapFunction<T extends IEvaluation> - Class in org.deeplearning4j.spark.impl.multilayer.evaluation
-
Function to evaluate data (using an IEvaluation instance), in a distributed manner
Flat map function used to batch examples for computational efficiency + reduce number of IEvaluation objects returned
for network efficiency.
- IEvaluateFlatMapFunction(boolean, Broadcast<String>, Broadcast<INDArray>, int, T...) - Constructor for class org.deeplearning4j.spark.impl.multilayer.evaluation.IEvaluateFlatMapFunction
-
- IEvaluateMDSFlatMapFunction<T extends IEvaluation> - Class in org.deeplearning4j.spark.impl.graph.evaluation
-
Function to evaluate data (using one or more IEvaluation instances), in a distributed manner
Flat map function used to batch examples for computational efficiency + reduce number of IEvaluation objects returned
for network efficiency.
- IEvaluateMDSFlatMapFunction(Broadcast<String>, Broadcast<INDArray>, int, T...) - Constructor for class org.deeplearning4j.spark.impl.graph.evaluation.IEvaluateMDSFlatMapFunction
-
- IEvaluation<T extends IEvaluation> - Interface in org.deeplearning4j.eval
-
- IEvaluationReduceFunction<T extends IEvaluation> - Class in org.deeplearning4j.spark.impl.multilayer.evaluation
-
- IEvaluationReduceFunction() - Constructor for class org.deeplearning4j.spark.impl.multilayer.evaluation.IEvaluationReduceFunction
-
- IGraph<V,E> - Interface in org.deeplearning4j.graph.api
-
Interface for a IGraph, with objects for each vertex and edge.
- IGraph<V extends SequenceElement,E extends Number> - Interface in org.deeplearning4j.models.sequencevectors.graph.primitives
-
Interface for a IGraph, with objects for each vertex and edge.
- ImageNetLabels - Class in org.deeplearning4j.zoo.util.imagenet
-
Helper class with a static method that returns the label description.
- ImageNetLabels() - Constructor for class org.deeplearning4j.zoo.util.imagenet.ImageNetLabels
-
- imageTransform - Variable in class org.deeplearning4j.datasets.iterator.impl.CifarDataSetIterator
-
- importKerasModelAndWeights(InputStream, boolean) - Static method in class org.deeplearning4j.nn.modelimport.keras.KerasModelImport
-
Load Keras (Functional API) Model saved using model.save_model(...).
- importKerasModelAndWeights(InputStream) - Static method in class org.deeplearning4j.nn.modelimport.keras.KerasModelImport
-
Load Keras (Functional API) Model saved using model.save_model(...).
- importKerasModelAndWeights(String, int[], boolean) - Static method in class org.deeplearning4j.nn.modelimport.keras.KerasModelImport
-
Load Keras (Functional API) Model saved using model.save_model(...).
- importKerasModelAndWeights(String, boolean) - Static method in class org.deeplearning4j.nn.modelimport.keras.KerasModelImport
-
Load Keras (Functional API) Model saved using model.save_model(...).
- importKerasModelAndWeights(String) - Static method in class org.deeplearning4j.nn.modelimport.keras.KerasModelImport
-
Load Keras (Functional API) Model saved using model.save_model(...).
- importKerasModelAndWeights(String, String, boolean) - Static method in class org.deeplearning4j.nn.modelimport.keras.KerasModelImport
-
Load Keras (Functional API) Model for which the configuration and weights were
saved separately using calls to model.to_json() and model.save_weights(...).
- importKerasModelAndWeights(String, String) - Static method in class org.deeplearning4j.nn.modelimport.keras.KerasModelImport
-
Load Keras (Functional API) Model for which the configuration and weights were
saved separately using calls to model.to_json() and model.save_weights(...).
- importKerasModelConfiguration(String, boolean) - Static method in class org.deeplearning4j.nn.modelimport.keras.KerasModelImport
-
Load Keras (Functional API) Model for which the configuration was saved
separately using calls to model.to_json() and model.save_weights(...).
- importKerasModelConfiguration(String) - Static method in class org.deeplearning4j.nn.modelimport.keras.KerasModelImport
-
Load Keras (Functional API) Model for which the configuration was saved
separately using calls to model.to_json() and model.save_weights(...).
- importKerasSequentialConfiguration(String, boolean) - Static method in class org.deeplearning4j.nn.modelimport.keras.KerasModelImport
-
Load Keras Sequential model for which the configuration was saved
separately using calls to model.to_json() and model.save_weights(...).
- importKerasSequentialConfiguration(String) - Static method in class org.deeplearning4j.nn.modelimport.keras.KerasModelImport
-
Load Keras Sequential model for which the configuration was saved
separately using calls to model.to_json() and model.save_weights(...).
- importKerasSequentialModelAndWeights(InputStream, boolean) - Static method in class org.deeplearning4j.nn.modelimport.keras.KerasModelImport
-
Load Keras Sequential model saved using model.save_model(...).
- importKerasSequentialModelAndWeights(InputStream) - Static method in class org.deeplearning4j.nn.modelimport.keras.KerasModelImport
-
Load Keras Sequential model saved using model.save_model(...).
- importKerasSequentialModelAndWeights(String, int[], boolean) - Static method in class org.deeplearning4j.nn.modelimport.keras.KerasModelImport
-
Load Keras Sequential model saved using model.save_model(...).
- importKerasSequentialModelAndWeights(String, boolean) - Static method in class org.deeplearning4j.nn.modelimport.keras.KerasModelImport
-
Load Keras Sequential model saved using model.save_model(...).
- importKerasSequentialModelAndWeights(String) - Static method in class org.deeplearning4j.nn.modelimport.keras.KerasModelImport
-
Load Keras Sequential model saved using model.save_model(...).
- importKerasSequentialModelAndWeights(String, String, boolean) - Static method in class org.deeplearning4j.nn.modelimport.keras.KerasModelImport
-
Load Keras Sequential model for which the configuration and weights were
saved separately using calls to model.to_json() and model.save_weights(...).
- importKerasSequentialModelAndWeights(String, String) - Static method in class org.deeplearning4j.nn.modelimport.keras.KerasModelImport
-
Load Keras Sequential model for which the configuration and weights were
saved separately using calls to model.to_json() and model.save_weights(...).
- importVocabulary(VocabCache<T>) - Method in class org.deeplearning4j.models.word2vec.wordstore.inmemory.AbstractCache
-
This method imports all elements from VocabCache passed as argument
If element already exists,
- importVocabulary(VocabCache<VocabWord>) - Method in class org.deeplearning4j.models.word2vec.wordstore.inmemory.InMemoryLookupCache
-
Deprecated.
- importVocabulary(VocabCache<T>) - Method in interface org.deeplearning4j.models.word2vec.wordstore.VocabCache
-
imports vocabulary
- importWeights(Hdf5Archive, String, Map<String, KerasLayer>, int, String) - Static method in class org.deeplearning4j.nn.modelimport.keras.utils.KerasModelUtils
-
Store weights to import with each associated Keras layer.
- inboundLayerNames - Variable in class org.deeplearning4j.nn.modelimport.keras.KerasLayer
-
- InceptionResNetHelper - Class in org.deeplearning4j.zoo.model.helper
-
Inception is based on GoogleLeNet configuration of convolutional layers for optimization of
resources and learning.
- InceptionResNetHelper() - Constructor for class org.deeplearning4j.zoo.model.helper.InceptionResNetHelper
-
- InceptionResNetV1 - Class in org.deeplearning4j.zoo.model
-
A variant of the original FaceNet model that relies on embeddings and triplet loss.
- inceptionV1ResA(ComputationGraphConfiguration.GraphBuilder, String, int, double, String) - Static method in class org.deeplearning4j.zoo.model.helper.InceptionResNetHelper
-
Append Inception-ResNet A to a computation graph.
- inceptionV1ResB(ComputationGraphConfiguration.GraphBuilder, String, int, double, String) - Static method in class org.deeplearning4j.zoo.model.helper.InceptionResNetHelper
-
Append Inception-ResNet B to a computation graph.
- inceptionV1ResC(ComputationGraphConfiguration.GraphBuilder, String, int, double, String) - Static method in class org.deeplearning4j.zoo.model.helper.InceptionResNetHelper
-
Append Inception-ResNet C to a computation graph.
- increaseElementFrequency(int) - Method in class org.deeplearning4j.models.sequencevectors.sequence.SequenceElement
-
Increases element frequency counter by argument
- increment() - Method in class org.deeplearning4j.models.word2vec.VocabWork
-
- incrementAll(Counter<T>) - Method in class org.deeplearning4j.spark.models.sequencevectors.primitives.ExtraCounter
-
- incrementCount(T, T, double) - Method in class org.deeplearning4j.models.glove.count.CountMap
-
- incrementCount() - Method in class org.deeplearning4j.models.word2vec.wordstore.VocabularyWord
-
- incrementDocCount(String, long) - Method in class org.deeplearning4j.models.word2vec.wordstore.inmemory.AbstractCache
-
Increment number of documents the label was observed in
Please note: this method is NOT thread-safe
- incrementDocCount(String, long) - Method in class org.deeplearning4j.models.word2vec.wordstore.inmemory.InMemoryLookupCache
-
Deprecated.
- incrementDocCount(String, long) - Method in interface org.deeplearning4j.models.word2vec.wordstore.VocabCache
-
Increment the document count
- incrementElementFrequency() - Method in class org.deeplearning4j.models.sequencevectors.sequence.SequenceElement
-
Increases element frequency counter by 1
- incrementEpochCount() - Method in class org.deeplearning4j.nn.graph.ComputationGraph
-
- incrementEpochCount() - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
-
- incrementFalseNegatives(Integer) - Method in class org.deeplearning4j.eval.Evaluation
-
- incrementFalsePositive(long) - Method in class org.deeplearning4j.eval.ROC.CountsForThreshold
-
- incrementFalsePositives(Integer) - Method in class org.deeplearning4j.eval.Evaluation
-
- incrementIteration() - Method in class org.deeplearning4j.parallelism.EarlyStoppingParallelTrainer
-
- incrementIterationCount(Model, int) - Static method in class org.deeplearning4j.optimize.solvers.BaseOptimizer
-
- incrementRetentionStep() - Method in class org.deeplearning4j.models.word2vec.wordstore.VocabularyWord
-
- incrementSequencesCount() - Method in class org.deeplearning4j.models.sequencevectors.sequence.SequenceElement
-
Increments document count by one
- incrementSequencesCount(long) - Method in class org.deeplearning4j.models.sequencevectors.sequence.SequenceElement
-
Increments document count by specified value
- incrementTotalDocCount() - Method in class org.deeplearning4j.models.word2vec.wordstore.inmemory.AbstractCache
-
Increment total number of documents observed by 1
- incrementTotalDocCount(long) - Method in class org.deeplearning4j.models.word2vec.wordstore.inmemory.AbstractCache
-
Increment total number of documents observed by specified value
- incrementTotalDocCount() - Method in class org.deeplearning4j.models.word2vec.wordstore.inmemory.InMemoryLookupCache
-
Deprecated.
- incrementTotalDocCount(long) - Method in class org.deeplearning4j.models.word2vec.wordstore.inmemory.InMemoryLookupCache
-
Deprecated.
- incrementTotalDocCount() - Method in interface org.deeplearning4j.models.word2vec.wordstore.VocabCache
-
Increment the doc count
- incrementTotalDocCount(long) - Method in interface org.deeplearning4j.models.word2vec.wordstore.VocabCache
-
Increment the doc count
- incrementTrueNegatives(Integer) - Method in class org.deeplearning4j.eval.Evaluation
-
- incrementTruePositive(long) - Method in class org.deeplearning4j.eval.ROC.CountsForThreshold
-
- incrementTruePositives(Integer) - Method in class org.deeplearning4j.eval.Evaluation
-
- incrementWordCount(String) - Method in class org.deeplearning4j.models.word2vec.wordstore.inmemory.AbstractCache
-
Increment frequency for specified label by 1
- incrementWordCount(String, int) - Method in class org.deeplearning4j.models.word2vec.wordstore.inmemory.AbstractCache
-
Increment frequency for specified label by specified value
- incrementWordCount(String) - Method in class org.deeplearning4j.models.word2vec.wordstore.inmemory.InMemoryLookupCache
-
Deprecated.
Increment the count for the given word
- incrementWordCount(String, int) - Method in class org.deeplearning4j.models.word2vec.wordstore.inmemory.InMemoryLookupCache
-
Deprecated.
Increment the count for the given word by
the amount increment
- incrementWordCount(String) - Method in interface org.deeplearning4j.models.word2vec.wordstore.VocabCache
-
Increment the count for the given word
- incrementWordCount(String, int) - Method in interface org.deeplearning4j.models.word2vec.wordstore.VocabCache
-
Increment the count for the given word by
the amount increment
- incrementWordCounter(String) - Method in class org.deeplearning4j.models.word2vec.wordstore.VocabularyHolder
-
Increments by one number of occurencies of the word in corpus
- INDArrayDataSetIterator - Class in org.deeplearning4j.datasets.iterator
-
- INDArrayDataSetIterator(Iterable<Pair<INDArray, INDArray>>, int) - Constructor for class org.deeplearning4j.datasets.iterator.INDArrayDataSetIterator
-
- index - Variable in class org.ansj.domain.Nature
-
- index - Variable in class org.deeplearning4j.bagofwords.vectorizer.BaseTextVectorizer
-
- index - Variable in class org.deeplearning4j.bagofwords.vectorizer.Builder
-
Deprecated.
- index(InvertedIndex) - Method in class org.deeplearning4j.bagofwords.vectorizer.Builder
-
Deprecated.
- index(InvertedIndex<VocabWord>) - Method in class org.deeplearning4j.models.paragraphvectors.ParagraphVectors.Builder
-
- index - Variable in class org.deeplearning4j.models.sequencevectors.sequence.SequenceElement
-
- index(InvertedIndex<VocabWord>) - Method in class org.deeplearning4j.models.word2vec.Word2Vec.Builder
-
Deprecated.
- index - Variable in class org.deeplearning4j.nn.layers.AbstractLayer
-
- index - Variable in class org.deeplearning4j.nn.layers.normalization.BatchNormalization
-
- index - Variable in class org.deeplearning4j.nn.layers.variational.VariationalAutoencoder
-
- index - Variable in class org.deeplearning4j.optimize.solvers.accumulation.EncodedGradientsAccumulator
-
- IndexAnalysis - Class in org.ansj.splitWord.analysis
-
用于检索的分词方式
- IndexAnalysis() - Constructor for class org.ansj.splitWord.analysis.IndexAnalysis
-
- IndexAnalysis(Reader) - Constructor for class org.ansj.splitWord.analysis.IndexAnalysis
-
- indexOf(String) - Method in interface org.deeplearning4j.models.embeddings.wordvectors.WordVectors
-
- indexOf(String) - Method in class org.deeplearning4j.models.embeddings.wordvectors.WordVectorsImpl
-
- indexOf(String) - Method in class org.deeplearning4j.models.word2vec.StaticWord2Vec
-
- indexOf(String) - Method in class org.deeplearning4j.models.word2vec.wordstore.inmemory.AbstractCache
-
Returns Huffman index for specified label
- indexOf(String) - Method in class org.deeplearning4j.models.word2vec.wordstore.inmemory.InMemoryLookupCache
-
Deprecated.
Returns the index of a given word
- indexOf(String) - Method in interface org.deeplearning4j.models.word2vec.wordstore.VocabCache
-
Returns the index of a given word
- indexOf(String) - Method in class org.deeplearning4j.models.word2vec.wordstore.VocabularyHolder
-
This method returns index of word in sorted list.
- indexOf(String) - Method in class org.deeplearning4j.text.documentiterator.LabelsSource
-
- indices - Variable in class org.deeplearning4j.clustering.vptree.VPTree.NodeBuilder
-
- inequalityHandling - Variable in class org.deeplearning4j.datasets.iterator.parallel.BaseParallelDataSetIterator
-
- InferenceCallable(VocabCache<VocabWord>, TokenizerFactory, LabelledDocument) - Constructor for class org.deeplearning4j.models.paragraphvectors.ParagraphVectors.InferenceCallable
-
- InferenceCallable(VocabCache<VocabWord>, TokenizerFactory, LabelledDocument, AtomicLong) - Constructor for class org.deeplearning4j.models.paragraphvectors.ParagraphVectors.InferenceCallable
-
- inferenceExecutor - Variable in class org.deeplearning4j.models.paragraphvectors.ParagraphVectors
-
- inferenceLocker - Variable in class org.deeplearning4j.models.paragraphvectors.ParagraphVectors
-
- InferenceMode - Enum in org.deeplearning4j.parallelism.inference
-
- inferenceMode(InferenceMode) - Method in class org.deeplearning4j.parallelism.ParallelInference.Builder
-
This method allows you to define mode that'll be used during inference.
- InferenceObservable - Interface in org.deeplearning4j.parallelism.inference
-
- inferenceWorkspaceMode - Variable in class org.deeplearning4j.nn.conf.ComputationGraphConfiguration
-
- inferenceWorkspaceMode - Variable in class org.deeplearning4j.nn.conf.MultiLayerConfiguration.Builder
-
- inferenceWorkspaceMode(WorkspaceMode) - Method in class org.deeplearning4j.nn.conf.MultiLayerConfiguration.Builder
-
- inferenceWorkspaceMode - Variable in class org.deeplearning4j.nn.conf.MultiLayerConfiguration
-
- inferenceWorkspaceMode - Variable in class org.deeplearning4j.nn.conf.NeuralNetConfiguration.Builder
-
- inferenceWorkspaceMode(WorkspaceMode) - Method in class org.deeplearning4j.nn.conf.NeuralNetConfiguration.Builder
-
This method defines Workspace mode being used during inference:
NONE: workspace won't be used
ENABLED: workspaces will be used for inference (reduced memory and better performance)
- inferenceWorkspaceMode(WorkspaceMode) - Method in class org.deeplearning4j.nn.transferlearning.FineTuneConfiguration.Builder
-
This method defines Workspace mode being used during inference:
NONE: workspace won't be used
ENABLED: workspaces will be used for inference (reduced memory and better performance)
- inferenceWorkspaceMode - Variable in class org.deeplearning4j.nn.transferlearning.FineTuneConfiguration
-
- inferInputLength(boolean) - Method in class org.deeplearning4j.nn.conf.layers.EmbeddingSequenceLayer.Builder
-
Set input sequence inference mode for embedding layer.
- inferInputType(INDArray) - Static method in class org.deeplearning4j.nn.conf.inputs.InputType
-
- inferInputTypes(INDArray...) - Static method in class org.deeplearning4j.nn.conf.inputs.InputType
-
- inferSequence(Sequence<T>, long, double, double, int) - Method in class org.deeplearning4j.models.embeddings.learning.impl.sequence.DBOW
-
This method does training on previously unseen paragraph, and returns inferred vector
- inferSequence(Sequence<T>, long, double, double, int) - Method in class org.deeplearning4j.models.embeddings.learning.impl.sequence.DM
-
This method does training on previously unseen paragraph, and returns inferred vector
- inferSequence(Sequence<T>, long, double, double, int) - Method in interface org.deeplearning4j.models.embeddings.learning.SequenceLearningAlgorithm
-
This method does training on previously unseen paragraph, and returns inferred vector
- inferSequence(Sequence<ShallowSequenceElement>, long, double, double, int) - Method in class org.deeplearning4j.spark.models.sequencevectors.learning.sequence.BaseSparkSequenceLearningAlgorithm
-
- inferVector(Collection<Vertex<V>>) - Method in class org.deeplearning4j.models.node2vec.Node2Vec
-
Deprecated.
- inferVector(String, double, double, int) - Method in class org.deeplearning4j.models.paragraphvectors.ParagraphVectors
-
This method calculates inferred vector for given text
- inferVector(LabelledDocument, double, double, int) - Method in class org.deeplearning4j.models.paragraphvectors.ParagraphVectors
-
This method calculates inferred vector for given document
- inferVector(List<VocabWord>, double, double, int) - Method in class org.deeplearning4j.models.paragraphvectors.ParagraphVectors
-
This method calculates inferred vector for given document
- inferVector(String) - Method in class org.deeplearning4j.models.paragraphvectors.ParagraphVectors
-
This method calculates inferred vector for given text, with default parameters for learning rate and iterations
- inferVector(LabelledDocument) - Method in class org.deeplearning4j.models.paragraphvectors.ParagraphVectors
-
This method calculates inferred vector for given document, with default parameters for learning rate and iterations
- inferVector(List<VocabWord>) - Method in class org.deeplearning4j.models.paragraphvectors.ParagraphVectors
-
This method calculates inferred vector for given list of words, with default parameters for learning rate and iterations
- inferVectorBatched(LabelledDocument) - Method in class org.deeplearning4j.models.paragraphvectors.ParagraphVectors
-
This method implements batched inference, based on Java Future parallelism model.
- inferVectorBatched(String) - Method in class org.deeplearning4j.models.paragraphvectors.ParagraphVectors
-
This method implements batched inference, based on Java Future parallelism model.
- inferVectorBatched(List<String>) - Method in class org.deeplearning4j.models.paragraphvectors.ParagraphVectors
-
This method does inference on a given List<String>
- information(double[]) - Static method in class org.deeplearning4j.clustering.util.MathUtils
-
This returns the entropy for a given vector of probabilities.
- init(String[]) - Method in class org.ansj.domain.AnsjItem
-
- init(WeightLookupTable<T>) - Method in class org.deeplearning4j.models.embeddings.reader.impl.BasicModelUtils
-
- init(WeightLookupTable<T>) - Method in class org.deeplearning4j.models.embeddings.reader.impl.TreeModelUtils
-
- init(WeightLookupTable<T>) - Method in interface org.deeplearning4j.models.embeddings.reader.ModelUtils
-
This method implementations should accept given lookup table, and use them in further calls to interface methods
- init - Variable in class org.deeplearning4j.models.sequencevectors.sequence.SequenceElement
-
- init() - Method in class org.deeplearning4j.models.word2vec.StaticWord2Vec
-
Init method validates configuration defined using
- init() - Method in interface org.deeplearning4j.nn.api.Model
-
Init the model
- init() - Method in interface org.deeplearning4j.nn.api.NeuralNetwork
-
This method does initialization of model
PLEASE NOTE: All implementations should track own state, to avoid double spending
- init(NeuralNetConfiguration, INDArray, boolean) - Method in interface org.deeplearning4j.nn.api.ParamInitializer
-
Initialize the parameters
- init() - Method in class org.deeplearning4j.nn.graph.ComputationGraph
-
Initialize the ComputationGraph network
- init(INDArray, boolean) - Method in class org.deeplearning4j.nn.graph.ComputationGraph
-
Initialize the ComputationGraph, optionally with an existing parameters array.
- init() - Method in class org.deeplearning4j.nn.layers.AbstractLayer
-
Init the model
- init() - Method in class org.deeplearning4j.nn.layers.FrozenLayer
-
Init the model
- init(NeuralNetConfiguration, INDArray, boolean) - Method in class org.deeplearning4j.nn.layers.ocnn.OCNNParamInitializer
-
- init() - Method in class org.deeplearning4j.nn.layers.recurrent.BidirectionalLayer
-
- init() - Method in class org.deeplearning4j.nn.layers.variational.VariationalAutoencoder
-
Init the model
- init() - Method in class org.deeplearning4j.nn.layers.wrapper.BaseWrapperLayer
-
- init(SolrResourceLoader) - Method in class org.deeplearning4j.nn.modelexport.solr.ltr.model.ScoringModel
-
- init() - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
-
Initialize the MultiLayerNetwork.
- init(INDArray, boolean) - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
-
Initialize the MultiLayerNetwork, optionally with an existing parameters array.
- init(NeuralNetConfiguration, INDArray, boolean) - Method in class org.deeplearning4j.nn.params.BatchNormalizationParamInitializer
-
- init(NeuralNetConfiguration, INDArray, boolean) - Method in class org.deeplearning4j.nn.params.BidirectionalParamInitializer
-
- init(NeuralNetConfiguration, INDArray, boolean) - Method in class org.deeplearning4j.nn.params.CenterLossParamInitializer
-
- init(NeuralNetConfiguration, INDArray, boolean) - Method in class org.deeplearning4j.nn.params.Convolution3DParamInitializer
-
- init(NeuralNetConfiguration, INDArray, boolean) - Method in class org.deeplearning4j.nn.params.ConvolutionParamInitializer
-
- init(NeuralNetConfiguration, INDArray, boolean) - Method in class org.deeplearning4j.nn.params.DefaultParamInitializer
-
- init(NeuralNetConfiguration, INDArray, boolean) - Method in class org.deeplearning4j.nn.params.DepthwiseConvolutionParamInitializer
-
- init(NeuralNetConfiguration, INDArray, boolean) - Method in class org.deeplearning4j.nn.params.ElementWiseParamInitializer
-
Initialize the parameters
- init(NeuralNetConfiguration, INDArray, boolean) - Method in class org.deeplearning4j.nn.params.EmptyParamInitializer
-
- init(NeuralNetConfiguration, INDArray, boolean) - Method in class org.deeplearning4j.nn.params.FrozenLayerParamInitializer
-
- init(NeuralNetConfiguration, INDArray, boolean) - Method in class org.deeplearning4j.nn.params.FrozenLayerWithBackpropParamInitializer
-
- init(NeuralNetConfiguration, INDArray, boolean) - Method in class org.deeplearning4j.nn.params.GravesBidirectionalLSTMParamInitializer
-
- init(NeuralNetConfiguration, INDArray, boolean) - Method in class org.deeplearning4j.nn.params.GravesLSTMParamInitializer
-
- init(NeuralNetConfiguration, INDArray, boolean) - Method in class org.deeplearning4j.nn.params.LSTMParamInitializer
-
- init(NeuralNetConfiguration, INDArray, boolean) - Method in class org.deeplearning4j.nn.params.PretrainParamInitializer
-
- init(NeuralNetConfiguration, INDArray, boolean) - Method in class org.deeplearning4j.nn.params.SameDiffParamInitializer
-
- init(NeuralNetConfiguration, INDArray, boolean) - Method in class org.deeplearning4j.nn.params.SeparableConvolutionParamInitializer
-
- init(NeuralNetConfiguration, INDArray, boolean) - Method in class org.deeplearning4j.nn.params.SimpleRnnParamInitializer
-
- init(NeuralNetConfiguration, INDArray, boolean) - Method in class org.deeplearning4j.nn.params.VariationalAutoencoderParamInitializer
-
- init(NeuralNetConfiguration, INDArray, boolean) - Method in class org.deeplearning4j.nn.params.WrapperLayerParamInitializer
-
- init() - Method in class org.deeplearning4j.nn.updater.UpdaterBlock
-
- init(Model, Object...) - Method in class org.deeplearning4j.parallelism.factory.DefaultTrainerContext
-
Initialize the context
- init(Model, Object...) - Method in class org.deeplearning4j.parallelism.factory.SymmetricTrainerContext
-
Initialize the context
- init(Model, Object...) - Method in interface org.deeplearning4j.parallelism.factory.TrainerContext
-
Initialize the context
- init() - Method in class org.deeplearning4j.parallelism.ParallelInference
-
- init() - Method in class org.deeplearning4j.parallelism.ParallelWrapper
-
- init(Model, Object...) - Method in class org.deeplearning4j.parallelism.parameterserver.ParameterServerTrainerContext
-
Initialize the context
- init() - Method in class org.deeplearning4j.plot.BarnesHutTsne
-
Init the model
- init() - Method in class org.deeplearning4j.plot.Tsne
-
- init(VoidConfiguration, Transport, Storage, Clipboard) - Method in class org.deeplearning4j.spark.parameterserver.networking.SilentTrainingDriver
-
- init() - Method in class org.deeplearning4j.spark.parameterserver.pw.SharedTrainingWrapper
-
- init() - Method in interface org.deeplearning4j.zoo.InstantiableModel
-
- init() - Method in class org.deeplearning4j.zoo.model.AlexNet
-
- init() - Method in class org.deeplearning4j.zoo.model.Darknet19
-
- init() - Method in class org.deeplearning4j.zoo.model.FaceNetNN4Small2
-
- init() - Method in class org.deeplearning4j.zoo.model.InceptionResNetV1
-
- init() - Method in class org.deeplearning4j.zoo.model.LeNet
-
- init() - Method in class org.deeplearning4j.zoo.model.NASNet
-
- init() - Method in class org.deeplearning4j.zoo.model.ResNet50
-
- init() - Method in class org.deeplearning4j.zoo.model.SimpleCNN
-
- init() - Method in class org.deeplearning4j.zoo.model.SqueezeNet
-
- init() - Method in class org.deeplearning4j.zoo.model.TextGenerationLSTM
-
- init() - Method in class org.deeplearning4j.zoo.model.TinyYOLO
-
- init() - Method in class org.deeplearning4j.zoo.model.UNet
-
- init() - Method in class org.deeplearning4j.zoo.model.VGG16
-
- init() - Method in class org.deeplearning4j.zoo.model.VGG19
-
- init() - Method in class org.deeplearning4j.zoo.model.Xception
-
- init() - Method in class org.deeplearning4j.zoo.model.YOLO2
-
- initAdaGrad() - Method in class org.deeplearning4j.models.embeddings.inmemory.InMemoryLookupTable
-
- initBigramTables() - Static method in class org.ansj.util.MyStaticValue
-
词与词之间的关联表数据
- initCalled - Variable in class org.deeplearning4j.nn.graph.ComputationGraph
-
- initCalled - Variable in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
-
- initClusters() - Method in class org.deeplearning4j.clustering.algorithm.BaseClusteringAlgorithm
-
Initialize the
cluster centers at random
- initDone - Variable in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
-
- initExpTable() - Method in class org.deeplearning4j.models.embeddings.inmemory.InMemoryLookupTable
-
- initExpTable() - Method in class org.deeplearning4j.spark.models.embeddings.word2vec.Word2Vec
-
- InitFieldsPresentDecoder - Class in org.deeplearning4j.ui.stats.sbe
-
- InitFieldsPresentDecoder() - Constructor for class org.deeplearning4j.ui.stats.sbe.InitFieldsPresentDecoder
-
- InitFieldsPresentEncoder - Class in org.deeplearning4j.ui.stats.sbe
-
- InitFieldsPresentEncoder() - Constructor for class org.deeplearning4j.ui.stats.sbe.InitFieldsPresentEncoder
-
- initGradientsView() - Method in class org.deeplearning4j.nn.graph.ComputationGraph
-
This method: initializes the flattened gradients array (used in backprop) and sets the appropriate subset in all layers.
- initGradientsView() - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
-
This method: initializes the flattened gradients array (used in backprop) and sets the appropriate subset in all layers.
- initHolder(VocabCache<VocabWord>, double[], int) - Method in class org.deeplearning4j.spark.models.embeddings.word2vec.NegativeHolder
-
- initialClusterCount - Variable in class org.deeplearning4j.clustering.strategy.BaseClusteringStrategy
-
- initialize(ClusterSet, boolean) - Static method in class org.deeplearning4j.clustering.info.ClusterSetInfo
-
- initialize() - Method in class org.deeplearning4j.earlystopping.termination.BestScoreEpochTerminationCondition
-
- initialize() - Method in interface org.deeplearning4j.earlystopping.termination.EpochTerminationCondition
-
Initialize the epoch termination condition (often a no-op)
- initialize() - Method in class org.deeplearning4j.earlystopping.termination.InvalidScoreIterationTerminationCondition
-
- initialize() - Method in interface org.deeplearning4j.earlystopping.termination.IterationTerminationCondition
-
Initialize the iteration termination condition (sometimes a no-op)
- initialize() - Method in class org.deeplearning4j.earlystopping.termination.MaxEpochsTerminationCondition
-
- initialize() - Method in class org.deeplearning4j.earlystopping.termination.MaxScoreIterationTerminationCondition
-
- initialize() - Method in class org.deeplearning4j.earlystopping.termination.MaxTimeIterationTerminationCondition
-
- initialize() - Method in class org.deeplearning4j.earlystopping.termination.ScoreImprovementEpochTerminationCondition
-
- initialize(IGraph<V, E>) - Method in class org.deeplearning4j.graph.models.deepwalk.DeepWalk
-
Initialize the DeepWalk model with a given graph.
- initialize(int[]) - Method in class org.deeplearning4j.graph.models.deepwalk.DeepWalk
-
Initialize the DeepWalk model with a list of vertex degrees for a graph.
Specifically, graphVertexDegrees[i] represents the vertex degree of the ith vertex
vertex degrees are used to construct a binary (Huffman) tree, which is in turn used in
the hierarchical softmax implementation
- initialize() - Method in class org.deeplearning4j.models.sequencevectors.transformers.impl.GraphTransformer
-
This method handles required initialization for GraphTransformer
- initialize(GradientsAccumulator) - Method in class org.deeplearning4j.optimize.solvers.accumulation.EncodingHandler
-
- initialize(GradientsAccumulator) - Method in class org.deeplearning4j.optimize.solvers.accumulation.LocalHandler
-
- initialize(GradientsAccumulator) - Method in interface org.deeplearning4j.optimize.solvers.accumulation.MessageHandler
-
This method does initial configuration of given MessageHandler instance
- initialize(InputSplit) - Method in class org.deeplearning4j.spark.datavec.iterator.SparkSourceDummyReader
-
- initialize(Configuration, InputSplit) - Method in class org.deeplearning4j.spark.datavec.iterator.SparkSourceDummyReader
-
- initialize(UimaContext) - Method in class org.deeplearning4j.text.annotator.PoStagger
-
Initializes the current instance with the given context.
- initialize(UimaContext) - Method in class org.deeplearning4j.text.tokenization.tokenizer.ConcurrentTokenizer
-
Initializes the current instance with the given context.
- initializeConstraints(Layer.Builder<?>) - Method in class org.deeplearning4j.nn.conf.layers.GravesBidirectionalLSTM
-
Deprecated.
- initializeConstraints(Layer.Builder<?>) - Method in class org.deeplearning4j.nn.conf.layers.GravesLSTM
-
- initializeConstraints(Layer.Builder<?>) - Method in class org.deeplearning4j.nn.conf.layers.Layer
-
Initialize the weight constraints.
- initializeConstraints(Layer.Builder<?>) - Method in class org.deeplearning4j.nn.conf.layers.LSTM
-
- initializeConstraints(Layer.Builder<?>) - Method in class org.deeplearning4j.nn.conf.layers.SeparableConvolution2D
-
- initializeIterators(List<DataSetIterator>) - Method in class org.deeplearning4j.datasets.iterator.parallel.JointParallelDataSetIterator
-
- initializeParameters(Map<String, INDArray>) - Method in class org.deeplearning4j.nn.conf.layers.samediff.AbstractSameDiffLayer
-
Set the initial parameter values for this layer, if required
- initializer() - Method in class org.deeplearning4j.nn.conf.layers.ActivationLayer
-
- initializer() - Method in class org.deeplearning4j.nn.conf.layers.AutoEncoder
-
- initializer() - Method in class org.deeplearning4j.nn.conf.layers.BaseUpsamplingLayer
-
- initializer() - Method in class org.deeplearning4j.nn.conf.layers.BatchNormalization
-
- initializer() - Method in class org.deeplearning4j.nn.conf.layers.CenterLossOutputLayer
-
- initializer() - Method in class org.deeplearning4j.nn.conf.layers.CnnLossLayer
-
- initializer() - Method in class org.deeplearning4j.nn.conf.layers.Convolution3D
-
- initializer() - Method in class org.deeplearning4j.nn.conf.layers.ConvolutionLayer
-
- initializer() - Method in class org.deeplearning4j.nn.conf.layers.Deconvolution2D
-
- initializer() - Method in class org.deeplearning4j.nn.conf.layers.DenseLayer
-
- initializer() - Method in class org.deeplearning4j.nn.conf.layers.DepthwiseConvolution2D
-
- initializer() - Method in class org.deeplearning4j.nn.conf.layers.DropoutLayer
-
- initializer() - Method in class org.deeplearning4j.nn.conf.layers.EmbeddingLayer
-
- initializer() - Method in class org.deeplearning4j.nn.conf.layers.EmbeddingSequenceLayer
-
- initializer() - Method in class org.deeplearning4j.nn.conf.layers.GlobalPoolingLayer
-
- initializer() - Method in class org.deeplearning4j.nn.conf.layers.GravesBidirectionalLSTM
-
Deprecated.
- initializer() - Method in class org.deeplearning4j.nn.conf.layers.GravesLSTM
-
- initializer() - Method in class org.deeplearning4j.nn.conf.layers.Layer
-
- initializer() - Method in class org.deeplearning4j.nn.conf.layers.LocalResponseNormalization
-
- initializer() - Method in class org.deeplearning4j.nn.conf.layers.LossLayer
-
- initializer() - Method in class org.deeplearning4j.nn.conf.layers.LSTM
-
- initializer() - Method in class org.deeplearning4j.nn.conf.layers.misc.ElementWiseMultiplicationLayer
-
- initializer() - Method in class org.deeplearning4j.nn.conf.layers.misc.FrozenLayer
-
- initializer() - Method in class org.deeplearning4j.nn.conf.layers.misc.FrozenLayerWithBackprop
-
- initializer() - Method in class org.deeplearning4j.nn.conf.layers.NoParamLayer
-
- initializer() - Method in class org.deeplearning4j.nn.conf.layers.objdetect.Yolo2OutputLayer
-
- initializer() - Method in class org.deeplearning4j.nn.conf.layers.OutputLayer
-
- initializer() - Method in class org.deeplearning4j.nn.conf.layers.recurrent.Bidirectional
-
- initializer() - Method in class org.deeplearning4j.nn.conf.layers.recurrent.SimpleRnn
-
- initializer() - Method in class org.deeplearning4j.nn.conf.layers.RnnLossLayer
-
- initializer() - Method in class org.deeplearning4j.nn.conf.layers.RnnOutputLayer
-
- initializer() - Method in class org.deeplearning4j.nn.conf.layers.samediff.AbstractSameDiffLayer
-
- initializer() - Method in class org.deeplearning4j.nn.conf.layers.SeparableConvolution2D
-
- initializer() - Method in class org.deeplearning4j.nn.conf.layers.SpaceToBatchLayer
-
- initializer() - Method in class org.deeplearning4j.nn.conf.layers.SpaceToDepthLayer
-
- initializer() - Method in class org.deeplearning4j.nn.conf.layers.Subsampling3DLayer
-
- initializer() - Method in class org.deeplearning4j.nn.conf.layers.SubsamplingLayer
-
- initializer() - Method in class org.deeplearning4j.nn.conf.layers.util.MaskLayer
-
- initializer() - Method in class org.deeplearning4j.nn.conf.layers.variational.VariationalAutoencoder
-
- initializer() - Method in class org.deeplearning4j.nn.conf.layers.wrapper.BaseWrapperLayer
-
- initializer() - Method in class org.deeplearning4j.nn.conf.layers.ZeroPadding1DLayer
-
- initializer() - Method in class org.deeplearning4j.nn.conf.layers.ZeroPadding3DLayer
-
- initializer() - Method in class org.deeplearning4j.nn.conf.ocnn.OCNNOutputLayer
-
- initializeWorkspaces(long) - Method in class org.deeplearning4j.datasets.iterator.callbacks.InterleavedDataSetCallback
-
- initialMemory - Variable in class org.deeplearning4j.optimize.solvers.accumulation.EncodedGradientsAccumulator.Builder
-
- initialMemory - Variable in class org.deeplearning4j.optimize.solvers.accumulation.EncodedGradientsAccumulator
-
- initialMomentum - Variable in class org.deeplearning4j.plot.BarnesHutTsne
-
- initialMomentum - Variable in class org.deeplearning4j.plot.Tsne.Builder
-
- initialMomentum - Variable in class org.deeplearning4j.plot.Tsne
-
- initInference() - Method in class org.deeplearning4j.models.paragraphvectors.ParagraphVectors
-
- initLearners() - Method in class org.deeplearning4j.models.sequencevectors.SequenceVectors
-
- initNegative() - Method in class org.deeplearning4j.models.embeddings.inmemory.InMemoryLookupTable
-
- initOptimizer() - Method in class org.deeplearning4j.optimize.Solver
-
- initParams() - Method in interface org.deeplearning4j.nn.api.Model
-
- initParams() - Method in class org.deeplearning4j.nn.graph.ComputationGraph
-
- initParams() - Method in class org.deeplearning4j.nn.layers.AbstractLayer
-
- initParams() - Method in class org.deeplearning4j.nn.layers.BaseLayer
-
- initParams() - Method in class org.deeplearning4j.nn.layers.recurrent.BidirectionalLayer
-
- initParams() - Method in class org.deeplearning4j.nn.layers.variational.VariationalAutoencoder
-
- initParams() - Method in class org.deeplearning4j.nn.layers.wrapper.BaseWrapperLayer
-
- initParams() - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
-
- initParams() - Method in class org.deeplearning4j.plot.BarnesHutTsne
-
- initPretrained() - Method in class org.deeplearning4j.zoo.ZooModel
-
By default, will return a pretrained ImageNet if available.
- initPretrained(PretrainedType) - Method in class org.deeplearning4j.zoo.ZooModel
-
Returns a pretrained model for the given dataset, if available.
- initTypeClass() - Method in class org.deeplearning4j.ui.stats.sbe.StorageMetaDataDecoder
-
- initTypeClass(String) - Method in class org.deeplearning4j.ui.stats.sbe.StorageMetaDataEncoder
-
- initTypeClassCharacterEncoding() - Static method in class org.deeplearning4j.ui.stats.sbe.StorageMetaDataDecoder
-
- initTypeClassCharacterEncoding() - Static method in class org.deeplearning4j.ui.stats.sbe.StorageMetaDataEncoder
-
- initTypeClassHeaderLength() - Static method in class org.deeplearning4j.ui.stats.sbe.StorageMetaDataDecoder
-
- initTypeClassHeaderLength() - Static method in class org.deeplearning4j.ui.stats.sbe.StorageMetaDataEncoder
-
- initTypeClassId() - Static method in class org.deeplearning4j.ui.stats.sbe.StorageMetaDataDecoder
-
- initTypeClassId() - Static method in class org.deeplearning4j.ui.stats.sbe.StorageMetaDataEncoder
-
- initTypeClassLength() - Method in class org.deeplearning4j.ui.stats.sbe.StorageMetaDataDecoder
-
- initTypeClassMetaAttribute(MetaAttribute) - Static method in class org.deeplearning4j.ui.stats.sbe.StorageMetaDataDecoder
-
- initTypeClassMetaAttribute(MetaAttribute) - Static method in class org.deeplearning4j.ui.stats.sbe.StorageMetaDataEncoder
-
- initValue(String[]) - Method in class org.ansj.domain.AnsjItem
-
- initWeights(int, int, WeightInit, INDArray) - Method in class org.deeplearning4j.nn.conf.layers.samediff.AbstractSameDiffLayer
-
- initWeights(int[], float, float) - Static method in class org.deeplearning4j.nn.weights.WeightInitUtil
-
- initWeights(double, double, int[], WeightInit, Distribution, INDArray) - Static method in class org.deeplearning4j.nn.weights.WeightInitUtil
-
Initializes a matrix with the given weight initialization scheme.
- initWeights(double, double, int[], WeightInit, Distribution, char, INDArray) - Static method in class org.deeplearning4j.nn.weights.WeightInitUtil
-
- InMemoryGraphLookupTable - Class in org.deeplearning4j.graph.models.embeddings
-
A standard in-memory implementation of a lookup table for vector representations of the vertices in a graph
- InMemoryGraphLookupTable(int, int, BinaryTree, double) - Constructor for class org.deeplearning4j.graph.models.embeddings.InMemoryGraphLookupTable
-
- InMemoryLookupCache - Class in org.deeplearning4j.models.word2vec.wordstore.inmemory
-
Deprecated.
- InMemoryLookupCache() - Constructor for class org.deeplearning4j.models.word2vec.wordstore.inmemory.InMemoryLookupCache
-
Deprecated.
- InMemoryLookupCache(boolean) - Constructor for class org.deeplearning4j.models.word2vec.wordstore.inmemory.InMemoryLookupCache
-
Deprecated.
- InMemoryLookupTable<T extends SequenceElement> - Class in org.deeplearning4j.models.embeddings.inmemory
-
Default word lookup table
- InMemoryLookupTable() - Constructor for class org.deeplearning4j.models.embeddings.inmemory.InMemoryLookupTable
-
- InMemoryLookupTable(VocabCache<T>, int, boolean, double, Random, double, boolean) - Constructor for class org.deeplearning4j.models.embeddings.inmemory.InMemoryLookupTable
-
- InMemoryLookupTable(VocabCache<T>, int, boolean, double, Random, double) - Constructor for class org.deeplearning4j.models.embeddings.inmemory.InMemoryLookupTable
-
- InMemoryLookupTable.Builder<T extends SequenceElement> - Class in org.deeplearning4j.models.embeddings.inmemory
-
- InMemoryLookupTable.WeightIterator - Class in org.deeplearning4j.models.embeddings.inmemory
-
- InMemoryModelSaver<T extends Model> - Class in org.deeplearning4j.earlystopping.saver
-
Save the best (and latest) models for early stopping training to memory for later retrieval
Note: Assumes that network is cloneable via .clone() method
- InMemoryModelSaver() - Constructor for class org.deeplearning4j.earlystopping.saver.InMemoryModelSaver
-
- InMemoryStatsStorage - Class in org.deeplearning4j.ui.storage
-
A StatsStorage implementation that stores all data in memory.
- InMemoryStatsStorage() - Constructor for class org.deeplearning4j.ui.storage.InMemoryStatsStorage
-
- input() - Method in interface org.deeplearning4j.nn.api.Model
-
The input/feature matrix for the model
- input() - Method in class org.deeplearning4j.nn.graph.ComputationGraph
-
- input - Variable in class org.deeplearning4j.nn.layers.AbstractLayer
-
- input() - Method in class org.deeplearning4j.nn.layers.AbstractLayer
-
- input() - Method in class org.deeplearning4j.nn.layers.recurrent.BidirectionalLayer
-
- input - Variable in class org.deeplearning4j.nn.layers.variational.VariationalAutoencoder
-
- input() - Method in class org.deeplearning4j.nn.layers.variational.VariationalAutoencoder
-
- input() - Method in class org.deeplearning4j.nn.layers.wrapper.BaseWrapperLayer
-
- input - Variable in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
-
- input() - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
-
- input() - Method in class org.deeplearning4j.plot.BarnesHutTsne
-
- INPUT_CHANNELS - Static variable in class org.deeplearning4j.datasets.fetchers.TinyImageNetFetcher
-
- INPUT_HEIGHT - Static variable in class org.deeplearning4j.datasets.fetchers.TinyImageNetFetcher
-
- INPUT_KEY - Static variable in class org.deeplearning4j.nn.layers.samediff.SameDiffLayer
-
- INPUT_WEIGHT_KEY - Static variable in class org.deeplearning4j.nn.params.GravesLSTMParamInitializer
-
- INPUT_WEIGHT_KEY - Static variable in class org.deeplearning4j.nn.params.LSTMParamInitializer
-
- INPUT_WEIGHT_KEY_BACKWARDS - Static variable in class org.deeplearning4j.nn.params.GravesBidirectionalLSTMParamInitializer
-
- INPUT_WEIGHT_KEY_FORWARDS - Static variable in class org.deeplearning4j.nn.params.GravesBidirectionalLSTMParamInitializer
-
- INPUT_WIDTH - Static variable in class org.deeplearning4j.datasets.fetchers.TinyImageNetFetcher
-
- inputColumns() - Method in class org.deeplearning4j.datasets.datavec.RecordReaderDataSetIterator
-
- inputColumns() - Method in class org.deeplearning4j.datasets.datavec.SequenceRecordReaderDataSetIterator
-
- inputColumns() - Method in class org.deeplearning4j.datasets.iterator.AbstractDataSetIterator
-
Input columns for the dataset
- inputColumns() - Method in class org.deeplearning4j.datasets.iterator.AsyncDataSetIterator
-
Input columns for the dataset
- inputColumns() - Method in class org.deeplearning4j.datasets.iterator.AsyncShieldDataSetIterator
-
Input columns for the dataset
- inputColumns() - Method in class org.deeplearning4j.datasets.iterator.BaseDatasetIterator
-
- inputColumns() - Method in interface org.deeplearning4j.datasets.iterator.DataSetFetcher
-
Deprecated.
The length of a feature vector for an individual example
- inputColumns() - Method in class org.deeplearning4j.datasets.iterator.EarlyTerminationDataSetIterator
-
- inputColumns() - Method in class org.deeplearning4j.datasets.iterator.ExistingDataSetIterator
-
- inputColumns() - Method in class org.deeplearning4j.datasets.iterator.file.FileDataSetIterator
-
- inputColumns() - Method in class org.deeplearning4j.datasets.iterator.FileSplitDataSetIterator
-
- inputColumns() - Method in class org.deeplearning4j.datasets.iterator.impl.BenchmarkDataSetIterator
-
- inputColumns() - Method in class org.deeplearning4j.datasets.iterator.impl.ListDataSetIterator
-
- inputColumns() - Method in class org.deeplearning4j.datasets.iterator.IteratorDataSetIterator
-
- inputColumns() - Method in class org.deeplearning4j.datasets.iterator.MultiDataSetWrapperIterator
-
- inputColumns() - Method in class org.deeplearning4j.datasets.iterator.MultipleEpochsIterator
-
Deprecated.
Input columns for the dataset
- inputColumns() - Method in class org.deeplearning4j.datasets.iterator.parallel.BaseParallelDataSetIterator
-
- inputColumns() - Method in class org.deeplearning4j.datasets.iterator.ReconstructionDataSetIterator
-
Input columns for the dataset
- inputColumns() - Method in class org.deeplearning4j.datasets.iterator.SamplingDataSetIterator
-
- inputColumns() - Method in class org.deeplearning4j.datasets.iterator.WorkspacesShieldDataSetIterator
-
- inputColumns() - Method in class org.deeplearning4j.datasets.test.TestDataSetIterator
-
- inputColumns() - Method in class org.deeplearning4j.iterator.CnnSentenceDataSetIterator
-
- inputColumns() - Method in class org.deeplearning4j.models.word2vec.iterator.Word2VecDataFetcher
-
- inputColumns() - Method in class org.deeplearning4j.models.word2vec.iterator.Word2VecDataSetIterator
-
- inputColumns - Variable in class org.deeplearning4j.spark.iterator.BaseDataSetIterator
-
- inputColumns() - Method in class org.deeplearning4j.spark.iterator.BaseDataSetIterator
-
- inputColumns() - Method in class org.deeplearning4j.spark.parameterserver.iterators.VirtualDataSetIterator
-
- inputDepth - Variable in class org.deeplearning4j.nn.conf.preprocessor.Cnn3DToFeedForwardPreProcessor
-
- inputFormat(String) - Method in class org.deeplearning4j.streaming.routes.CamelKafkaRouteBuilder.Builder
-
- inputHeight - Variable in class org.deeplearning4j.nn.conf.preprocessor.Cnn3DToFeedForwardPreProcessor
-
- inputHeight - Variable in class org.deeplearning4j.nn.conf.preprocessor.CnnToFeedForwardPreProcessor
-
- InputHomogenization - Class in org.deeplearning4j.text.inputsanitation
-
Performs some very basic textual transformations
such as word shape, lower casing, and stripping of punctuation
- InputHomogenization(String) - Constructor for class org.deeplearning4j.text.inputsanitation.InputHomogenization
-
Input text to applyTransformToOrigin
- InputHomogenization(String, boolean) - Constructor for class org.deeplearning4j.text.inputsanitation.InputHomogenization
-
- InputHomogenization(String, List<String>) - Constructor for class org.deeplearning4j.text.inputsanitation.InputHomogenization
-
- inputLayerNames - Variable in class org.deeplearning4j.nn.modelimport.keras.KerasModel
-
- inputLength(int) - Method in class org.deeplearning4j.nn.conf.layers.EmbeddingSequenceLayer.Builder
-
Set input sequence length for this embedding layer.
- inputMaskArray - Variable in class org.deeplearning4j.nn.layers.BaseOutputLayer
-
- inputMaskArrayState - Variable in class org.deeplearning4j.nn.layers.BaseOutputLayer
-
- inputPreProcessor(String, InputPreProcessor) - Method in class org.deeplearning4j.nn.conf.ComputationGraphConfiguration.GraphBuilder
-
- InputPreProcessor - Interface in org.deeplearning4j.nn.conf
-
Input pre processor used
for pre processing input before passing it
to the neural network.
- inputPreProcessor(Integer, InputPreProcessor) - Method in class org.deeplearning4j.nn.conf.MultiLayerConfiguration.Builder
-
Specify the processors.
- inputPreProcessors - Variable in class org.deeplearning4j.nn.conf.ComputationGraphConfiguration.GraphBuilder
-
- inputPreProcessors - Variable in class org.deeplearning4j.nn.conf.MultiLayerConfiguration.Builder
-
- inputPreProcessors(Map<Integer, InputPreProcessor>) - Method in class org.deeplearning4j.nn.conf.MultiLayerConfiguration.Builder
-
- inputPreProcessors - Variable in class org.deeplearning4j.nn.conf.MultiLayerConfiguration
-
- inputs - Variable in class org.deeplearning4j.nn.graph.vertex.BaseGraphVertex
-
- inputShape - Variable in class org.deeplearning4j.nn.modelimport.keras.KerasLayer
-
- inputShape - Variable in class org.deeplearning4j.nn.modelimport.keras.utils.KerasModelBuilder
-
- inputShape(int[]) - Method in class org.deeplearning4j.nn.modelimport.keras.utils.KerasModelBuilder
-
- InputStreamCreator - Interface in org.deeplearning4j.models.word2vec
-
Created by agibsonccc on 10/19/14.
- InputType - Class in org.deeplearning4j.nn.conf.inputs
-
The InputType class is used to track and define the types of activations etc used in a ComputationGraph.
- InputType() - Constructor for class org.deeplearning4j.nn.conf.inputs.InputType
-
- inputType - Variable in class org.deeplearning4j.nn.conf.MultiLayerConfiguration.Builder
-
- inputType() - Method in class org.deeplearning4j.nn.conf.NeuralNetConfiguration.ListBuilder
-
A convenience method for setting input types: note that for example .inputType().convolutional(h,w,d)
is equivalent to .setInputType(InputType.convolutional(h,w,d))
- InputType.InputTypeConvolutional - Class in org.deeplearning4j.nn.conf.inputs
-
- InputType.InputTypeConvolutional3D - Class in org.deeplearning4j.nn.conf.inputs
-
- InputType.InputTypeConvolutionalFlat - Class in org.deeplearning4j.nn.conf.inputs
-
- InputType.InputTypeFeedForward - Class in org.deeplearning4j.nn.conf.inputs
-
- InputType.InputTypeRecurrent - Class in org.deeplearning4j.nn.conf.inputs
-
- InputType.Type - Enum in org.deeplearning4j.nn.conf.inputs
-
The type of activations in/out of a given GraphVertex
FF: Standard feed-foward (2d minibatch, 1d per example) data
RNN: Recurrent neural network (3d minibatch) time series data
CNN: 2D Convolutional neural network (4d minibatch, [miniBatchSize, channels, height, width])
CNNFlat: Flattened 2D conv net data (2d minibatch, [miniBatchSize, height * width * channels])
CNN3D: 3D convolutional neural network (5d minibatch, [miniBatchSize, channels, height, width, channels])
- InputTypeBuilder() - Constructor for class org.deeplearning4j.nn.conf.NeuralNetConfiguration.ListBuilder.InputTypeBuilder
-
- InputTypeConvolutional() - Constructor for class org.deeplearning4j.nn.conf.inputs.InputType.InputTypeConvolutional
-
- InputTypeConvolutional3D() - Constructor for class org.deeplearning4j.nn.conf.inputs.InputType.InputTypeConvolutional3D
-
- InputTypeConvolutionalFlat() - Constructor for class org.deeplearning4j.nn.conf.inputs.InputType.InputTypeConvolutionalFlat
-
- InputTypeFeedForward() - Constructor for class org.deeplearning4j.nn.conf.inputs.InputType.InputTypeFeedForward
-
- InputTypeRecurrent(int) - Constructor for class org.deeplearning4j.nn.conf.inputs.InputType.InputTypeRecurrent
-
- InputTypeUtil - Class in org.deeplearning4j.nn.conf.layers
-
Utilities for calculating input types
- InputTypeUtil() - Constructor for class org.deeplearning4j.nn.conf.layers.InputTypeUtil
-
- inputUri(String) - Method in class org.deeplearning4j.streaming.routes.CamelKafkaRouteBuilder.Builder
-
- inputUris - Variable in class org.deeplearning4j.BasePipeline
-
- inputUris() - Method in class org.deeplearning4j.BasePipeline
-
- inputUris() - Method in interface org.deeplearning4j.Pipeline
-
Origin data
- inputUris() - Method in class org.deeplearning4j.StreamingPipeline
-
- InputVertex - Class in org.deeplearning4j.nn.graph.vertex.impl
-
An InputVertex simply defines the location (and connection structure) of inputs to the ComputationGraph.
- InputVertex(ComputationGraph, String, int, VertexIndices[]) - Constructor for class org.deeplearning4j.nn.graph.vertex.impl.InputVertex
-
- inputVertices - Variable in class org.deeplearning4j.nn.graph.vertex.BaseGraphVertex
-
A representation of the vertices that are inputs to this vertex (inputs during forward pass)
Specifically, if inputVertices[X].getVertexIndex() = Y, and inputVertices[X].getVertexEdgeNumber() = Z
then the Zth output of vertex Y is the Xth input to this vertex
- inputWeightConstraints - Variable in class org.deeplearning4j.nn.conf.layers.BaseRecurrentLayer.Builder
-
- inputWidth - Variable in class org.deeplearning4j.nn.conf.preprocessor.Cnn3DToFeedForwardPreProcessor
-
- inputWidth - Variable in class org.deeplearning4j.nn.conf.preprocessor.CnnToFeedForwardPreProcessor
-
- insert(String, String...) - Static method in class org.ansj.library.AmbiguityLibrary
-
插入到树中呀
- insert(String, Value) - Static method in class org.ansj.library.AmbiguityLibrary
-
插入到树种
- insert(String, String, String, int) - Static method in class org.ansj.library.DicLibrary
-
关键词增加
- insert(String, String) - Static method in class org.ansj.library.DicLibrary
-
增加关键词
- insert(String, String[]) - Static method in class org.ansj.library.SynonymsLibrary
-
覆盖更新同义词 [中国, 中华, 我国] -> replace([中国,华夏]) -> [中国,华夏]
- insert(INDArray) - Method in class org.deeplearning4j.clustering.kdtree.KDTree
-
Insert a point in to the tree
- insert(int) - Method in class org.deeplearning4j.clustering.quadtree.QuadTree
-
Insert an index of the data in to the tree
- InsertedDictionary - Class in com.atilika.kuromoji.dict
-
- InsertedDictionary(int) - Constructor for class com.atilika.kuromoji.dict.InsertedDictionary
-
- insertedDictionary - Variable in class com.atilika.kuromoji.TokenizerBase.Builder
-
- insertStopNatures(String, String...) - Static method in class org.ansj.library.StopLibrary
-
词性过滤
- insertStopNatures(String...) - Method in class org.ansj.recognition.impl.StopRecognition
-
批量增加停用词性 比如 增加nr 后.人名将不在结果中
- insertStopRegexes(String, String...) - Static method in class org.ansj.library.StopLibrary
-
正则过滤
- insertStopRegexes(String...) - Method in class org.ansj.recognition.impl.StopRecognition
-
增加正则表达式过滤
- insertStopWords(String, String...) - Static method in class org.ansj.library.StopLibrary
-
增加停用词
- insertStopWords(String, List<String>) - Static method in class org.ansj.library.StopLibrary
-
增加停用词
- insertStopWords(Collection<String>) - Method in class org.ansj.recognition.impl.StopRecognition
-
批量增加停用词
- insertStopWords(String...) - Method in class org.ansj.recognition.impl.StopRecognition
-
批量增加停用词
- insertTerm(Term[], Term, TermUtil.InsertTermType) - Static method in class org.ansj.util.TermUtil
-
将一个term插入到链表中的对应位置中, 如果这个term已经存在参照type type 0.跳过 1.
- insertTerm(Term[], List<Term>, TermNatures) - Static method in class org.ansj.util.TermUtil
-
- insertTermNum(Term[], Term) - Static method in class org.ansj.util.TermUtil
-
- INSTANCE - Static variable in class org.deeplearning4j.spark.parameterserver.pw.SharedTrainingWrapper
-
- instanceBidPrice(Optional<Float>) - Method in class org.deeplearning4j.aws.emr.SparkEMRClient.Builder
-
The optional bid value for this cluster's spot instances
see https://docs.aws.amazon.com/AWSEC2/latest/UserGuide/how-spot-instances-work.html
Uses the on-demand market if empty.
- instanceCount(int) - Method in class org.deeplearning4j.aws.emr.SparkEMRClient.Builder
-
The number of instances this deployment should comprise of
- instanceRole(String) - Method in class org.deeplearning4j.aws.emr.SparkEMRClient.Builder
-
The EC2 instance role that this cluster's instances should assume
see https://docs.aws.amazon.com/AWSEC2/latest/UserGuide/iam-roles-for-amazon-ec2.html
- instanceType(String) - Method in class org.deeplearning4j.aws.emr.SparkEMRClient.Builder
-
The type of instance this cluster should comprise of
See https://aws.amazon.com/ec2/instance-types/
- InstantiableModel - Interface in org.deeplearning4j.zoo
-
Interface for defining a model that can be instantiated and return
information about itself.
- instantiate(ComputationGraph, String, int, INDArray, boolean) - Method in class org.deeplearning4j.nn.conf.graph.ElementWiseVertex
-
- instantiate(ComputationGraph, String, int, INDArray, boolean) - Method in class org.deeplearning4j.nn.conf.graph.FrozenVertex
-
- instantiate(ComputationGraph, String, int, INDArray, boolean) - Method in class org.deeplearning4j.nn.conf.graph.GraphVertex
-
Create a
GraphVertex instance, for the given computation graph,
given the configuration instance.
- instantiate(ComputationGraph, String, int, INDArray, boolean) - Method in class org.deeplearning4j.nn.conf.graph.L2NormalizeVertex
-
- instantiate(ComputationGraph, String, int, INDArray, boolean) - Method in class org.deeplearning4j.nn.conf.graph.L2Vertex
-
- instantiate(ComputationGraph, String, int, INDArray, boolean) - Method in class org.deeplearning4j.nn.conf.graph.LayerVertex
-
- instantiate(ComputationGraph, String, int, INDArray, boolean) - Method in class org.deeplearning4j.nn.conf.graph.MergeVertex
-
- instantiate(ComputationGraph, String, int, INDArray, boolean) - Method in class org.deeplearning4j.nn.conf.graph.PoolHelperVertex
-
- instantiate(ComputationGraph, String, int, INDArray, boolean) - Method in class org.deeplearning4j.nn.conf.graph.PreprocessorVertex
-
- instantiate(ComputationGraph, String, int, INDArray, boolean) - Method in class org.deeplearning4j.nn.conf.graph.ReshapeVertex
-
- instantiate(ComputationGraph, String, int, INDArray, boolean) - Method in class org.deeplearning4j.nn.conf.graph.rnn.DuplicateToTimeSeriesVertex
-
- instantiate(ComputationGraph, String, int, INDArray, boolean) - Method in class org.deeplearning4j.nn.conf.graph.rnn.LastTimeStepVertex
-
- instantiate(ComputationGraph, String, int, INDArray, boolean) - Method in class org.deeplearning4j.nn.conf.graph.rnn.ReverseTimeSeriesVertex
-
- instantiate(ComputationGraph, String, int, INDArray, boolean) - Method in class org.deeplearning4j.nn.conf.graph.ScaleVertex
-
- instantiate(ComputationGraph, String, int, INDArray, boolean) - Method in class org.deeplearning4j.nn.conf.graph.ShiftVertex
-
- instantiate(ComputationGraph, String, int, INDArray, boolean) - Method in class org.deeplearning4j.nn.conf.graph.StackVertex
-
- instantiate(ComputationGraph, String, int, INDArray, boolean) - Method in class org.deeplearning4j.nn.conf.graph.SubsetVertex
-
- instantiate(ComputationGraph, String, int, INDArray, boolean) - Method in class org.deeplearning4j.nn.conf.graph.UnstackVertex
-
- instantiate(NeuralNetConfiguration, Collection<TrainingListener>, int, INDArray, boolean) - Method in class org.deeplearning4j.nn.conf.layers.ActivationLayer
-
- instantiate(NeuralNetConfiguration, Collection<TrainingListener>, int, INDArray, boolean) - Method in class org.deeplearning4j.nn.conf.layers.AutoEncoder
-
- instantiate(NeuralNetConfiguration, Collection<TrainingListener>, int, INDArray, boolean) - Method in class org.deeplearning4j.nn.conf.layers.BatchNormalization
-
- instantiate(NeuralNetConfiguration, Collection<TrainingListener>, int, INDArray, boolean) - Method in class org.deeplearning4j.nn.conf.layers.CenterLossOutputLayer
-
- instantiate(NeuralNetConfiguration, Collection<TrainingListener>, int, INDArray, boolean) - Method in class org.deeplearning4j.nn.conf.layers.CnnLossLayer
-
- instantiate(NeuralNetConfiguration, Collection<TrainingListener>, int, INDArray, boolean) - Method in class org.deeplearning4j.nn.conf.layers.Convolution1DLayer
-
- instantiate(NeuralNetConfiguration, Collection<TrainingListener>, int, INDArray, boolean) - Method in class org.deeplearning4j.nn.conf.layers.Convolution3D
-
- instantiate(NeuralNetConfiguration, Collection<TrainingListener>, int, INDArray, boolean) - Method in class org.deeplearning4j.nn.conf.layers.convolutional.Cropping1D
-
- instantiate(NeuralNetConfiguration, Collection<TrainingListener>, int, INDArray, boolean) - Method in class org.deeplearning4j.nn.conf.layers.convolutional.Cropping2D
-
- instantiate(NeuralNetConfiguration, Collection<TrainingListener>, int, INDArray, boolean) - Method in class org.deeplearning4j.nn.conf.layers.convolutional.Cropping3D
-
- instantiate(NeuralNetConfiguration, Collection<TrainingListener>, int, INDArray, boolean) - Method in class org.deeplearning4j.nn.conf.layers.ConvolutionLayer
-
- instantiate(NeuralNetConfiguration, Collection<TrainingListener>, int, INDArray, boolean) - Method in class org.deeplearning4j.nn.conf.layers.Deconvolution2D
-
- instantiate(NeuralNetConfiguration, Collection<TrainingListener>, int, INDArray, boolean) - Method in class org.deeplearning4j.nn.conf.layers.DenseLayer
-
- instantiate(NeuralNetConfiguration, Collection<TrainingListener>, int, INDArray, boolean) - Method in class org.deeplearning4j.nn.conf.layers.DepthwiseConvolution2D
-
- instantiate(NeuralNetConfiguration, Collection<TrainingListener>, int, INDArray, boolean) - Method in class org.deeplearning4j.nn.conf.layers.DropoutLayer
-
- instantiate(NeuralNetConfiguration, Collection<TrainingListener>, int, INDArray, boolean) - Method in class org.deeplearning4j.nn.conf.layers.EmbeddingLayer
-
- instantiate(NeuralNetConfiguration, Collection<TrainingListener>, int, INDArray, boolean) - Method in class org.deeplearning4j.nn.conf.layers.EmbeddingSequenceLayer
-
- instantiate(NeuralNetConfiguration, Collection<TrainingListener>, int, INDArray, boolean) - Method in class org.deeplearning4j.nn.conf.layers.GlobalPoolingLayer
-
- instantiate(NeuralNetConfiguration, Collection<TrainingListener>, int, INDArray, boolean) - Method in class org.deeplearning4j.nn.conf.layers.GravesBidirectionalLSTM
-
Deprecated.
- instantiate(NeuralNetConfiguration, Collection<TrainingListener>, int, INDArray, boolean) - Method in class org.deeplearning4j.nn.conf.layers.GravesLSTM
-
- instantiate(NeuralNetConfiguration, Collection<TrainingListener>, int, INDArray, boolean) - Method in class org.deeplearning4j.nn.conf.layers.Layer
-
- instantiate(NeuralNetConfiguration, Collection<TrainingListener>, int, INDArray, boolean) - Method in class org.deeplearning4j.nn.conf.layers.LocalResponseNormalization
-
- instantiate(NeuralNetConfiguration, Collection<TrainingListener>, int, INDArray, boolean) - Method in class org.deeplearning4j.nn.conf.layers.LossLayer
-
- instantiate(NeuralNetConfiguration, Collection<TrainingListener>, int, INDArray, boolean) - Method in class org.deeplearning4j.nn.conf.layers.LSTM
-
- instantiate(NeuralNetConfiguration, Collection<TrainingListener>, int, INDArray, boolean) - Method in class org.deeplearning4j.nn.conf.layers.misc.ElementWiseMultiplicationLayer
-
- instantiate(NeuralNetConfiguration, Collection<TrainingListener>, int, INDArray, boolean) - Method in class org.deeplearning4j.nn.conf.layers.misc.FrozenLayer
-
- instantiate(NeuralNetConfiguration, Collection<TrainingListener>, int, INDArray, boolean) - Method in class org.deeplearning4j.nn.conf.layers.misc.FrozenLayerWithBackprop
-
- instantiate(NeuralNetConfiguration, Collection<TrainingListener>, int, INDArray, boolean) - Method in class org.deeplearning4j.nn.conf.layers.objdetect.Yolo2OutputLayer
-
- instantiate(NeuralNetConfiguration, Collection<TrainingListener>, int, INDArray, boolean) - Method in class org.deeplearning4j.nn.conf.layers.OutputLayer
-
- instantiate(NeuralNetConfiguration, Collection<TrainingListener>, int, INDArray, boolean) - Method in class org.deeplearning4j.nn.conf.layers.recurrent.Bidirectional
-
- instantiate(NeuralNetConfiguration, Collection<TrainingListener>, int, INDArray, boolean) - Method in class org.deeplearning4j.nn.conf.layers.recurrent.LastTimeStep
-
- instantiate(NeuralNetConfiguration, Collection<TrainingListener>, int, INDArray, boolean) - Method in class org.deeplearning4j.nn.conf.layers.recurrent.SimpleRnn
-
- instantiate(NeuralNetConfiguration, Collection<TrainingListener>, int, INDArray, boolean) - Method in class org.deeplearning4j.nn.conf.layers.RnnLossLayer
-
- instantiate(NeuralNetConfiguration, Collection<TrainingListener>, int, INDArray, boolean) - Method in class org.deeplearning4j.nn.conf.layers.RnnOutputLayer
-
- instantiate(NeuralNetConfiguration, Collection<TrainingListener>, int, INDArray, boolean) - Method in class org.deeplearning4j.nn.conf.layers.samediff.AbstractSameDiffLayer
-
- instantiate(NeuralNetConfiguration, Collection<TrainingListener>, int, INDArray, boolean) - Method in class org.deeplearning4j.nn.conf.layers.samediff.BaseSameDiffLayer
-
- instantiate(NeuralNetConfiguration, Collection<TrainingListener>, int, INDArray, boolean) - Method in class org.deeplearning4j.nn.conf.layers.SeparableConvolution2D
-
- instantiate(NeuralNetConfiguration, Collection<TrainingListener>, int, INDArray, boolean) - Method in class org.deeplearning4j.nn.conf.layers.SpaceToBatchLayer
-
- instantiate(NeuralNetConfiguration, Collection<TrainingListener>, int, INDArray, boolean) - Method in class org.deeplearning4j.nn.conf.layers.SpaceToDepthLayer
-
- instantiate(NeuralNetConfiguration, Collection<TrainingListener>, int, INDArray, boolean) - Method in class org.deeplearning4j.nn.conf.layers.Subsampling1DLayer
-
- instantiate(NeuralNetConfiguration, Collection<TrainingListener>, int, INDArray, boolean) - Method in class org.deeplearning4j.nn.conf.layers.Subsampling3DLayer
-
- instantiate(NeuralNetConfiguration, Collection<TrainingListener>, int, INDArray, boolean) - Method in class org.deeplearning4j.nn.conf.layers.SubsamplingLayer
-
- instantiate(NeuralNetConfiguration, Collection<TrainingListener>, int, INDArray, boolean) - Method in class org.deeplearning4j.nn.conf.layers.Upsampling1D
-
- instantiate(NeuralNetConfiguration, Collection<TrainingListener>, int, INDArray, boolean) - Method in class org.deeplearning4j.nn.conf.layers.Upsampling2D
-
- instantiate(NeuralNetConfiguration, Collection<TrainingListener>, int, INDArray, boolean) - Method in class org.deeplearning4j.nn.conf.layers.Upsampling3D
-
- instantiate(NeuralNetConfiguration, Collection<TrainingListener>, int, INDArray, boolean) - Method in class org.deeplearning4j.nn.conf.layers.util.MaskLayer
-
- instantiate(NeuralNetConfiguration, Collection<TrainingListener>, int, INDArray, boolean) - Method in class org.deeplearning4j.nn.conf.layers.util.MaskZeroLayer
-
- instantiate(NeuralNetConfiguration, Collection<TrainingListener>, int, INDArray, boolean) - Method in class org.deeplearning4j.nn.conf.layers.variational.VariationalAutoencoder
-
- instantiate(NeuralNetConfiguration, Collection<TrainingListener>, int, INDArray, boolean) - Method in class org.deeplearning4j.nn.conf.layers.ZeroPadding1DLayer
-
- instantiate(NeuralNetConfiguration, Collection<TrainingListener>, int, INDArray, boolean) - Method in class org.deeplearning4j.nn.conf.layers.ZeroPadding3DLayer
-
- instantiate(NeuralNetConfiguration, Collection<TrainingListener>, int, INDArray, boolean) - Method in class org.deeplearning4j.nn.conf.layers.ZeroPaddingLayer
-
- instantiate(NeuralNetConfiguration, Collection<TrainingListener>, int, INDArray, boolean) - Method in class org.deeplearning4j.nn.conf.ocnn.OCNNOutputLayer
-
- instantiateTokenizerFactory() - Method in class org.deeplearning4j.spark.models.sequencevectors.functions.BaseTokenizerFunction
-
- IntDoubleReduceFunction - Class in org.deeplearning4j.spark.impl.common.reduce
-
Add both elements of a Tuple2<Integer,Double>
- IntDoubleReduceFunction() - Constructor for class org.deeplearning4j.spark.impl.common.reduce.IntDoubleReduceFunction
-
- IntegerArrayIO - Class in com.atilika.kuromoji.io
-
- IntegerArrayIO() - Constructor for class com.atilika.kuromoji.io.IntegerArrayIO
-
- IntegerVertexFactory - Class in org.deeplearning4j.graph.vertexfactory
-
- IntegerVertexFactory() - Constructor for class org.deeplearning4j.graph.vertexfactory.IntegerVertexFactory
-
- interleavedCounter - Variable in class org.deeplearning4j.parallelism.MagicQueue
-
Deprecated.
- InterleavedDataSetCallback - Class in org.deeplearning4j.datasets.iterator.callbacks
-
This callback migrates incoming datasets in round-robin manner, to ensure TDA for ParallelWrapper
- InterleavedDataSetCallback(int) - Constructor for class org.deeplearning4j.datasets.iterator.callbacks.InterleavedDataSetCallback
-
- interleavedPutter - Variable in class org.deeplearning4j.parallelism.MagicQueue
-
Deprecated.
- intersection(Collection<T>, Collection<T>) - Static method in class org.deeplearning4j.clustering.util.SetUtils
-
- intersectionP(Set<? extends T>, Set<? extends T>) - Static method in class org.deeplearning4j.clustering.util.SetUtils
-
- Interval(double, double) - Constructor for class org.deeplearning4j.clustering.kdtree.HyperRect.Interval
-
- intializeConfigurations() - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
-
- IntPartitioner - Class in org.deeplearning4j.spark.data.shuffle
-
- IntPartitioner() - Constructor for class org.deeplearning4j.spark.data.shuffle.IntPartitioner
-
Deprecated.
- InvalidInputTypeException - Exception in org.deeplearning4j.nn.conf.inputs
-
InvalidInputTypeException: Thrown if the GraphVertex cannot handle the type of input provided.
- InvalidInputTypeException(String) - Constructor for exception org.deeplearning4j.nn.conf.inputs.InvalidInputTypeException
-
- InvalidInputTypeException(String, Throwable) - Constructor for exception org.deeplearning4j.nn.conf.inputs.InvalidInputTypeException
-
- InvalidInputTypeException(Throwable) - Constructor for exception org.deeplearning4j.nn.conf.inputs.InvalidInputTypeException
-
- InvalidKerasConfigurationException - Exception in org.deeplearning4j.nn.modelimport.keras.exceptions
-
Indicates that user is attempting to import a Keras model configuration that
is malformed or invalid in some other way.
- InvalidKerasConfigurationException(String) - Constructor for exception org.deeplearning4j.nn.modelimport.keras.exceptions.InvalidKerasConfigurationException
-
- InvalidKerasConfigurationException(String, Throwable) - Constructor for exception org.deeplearning4j.nn.modelimport.keras.exceptions.InvalidKerasConfigurationException
-
- InvalidKerasConfigurationException(Throwable) - Constructor for exception org.deeplearning4j.nn.modelimport.keras.exceptions.InvalidKerasConfigurationException
-
- InvalidScoreIterationTerminationCondition - Class in org.deeplearning4j.earlystopping.termination
-
Terminate training at this iteration if score is NaN or Infinite for the last minibatch
- InvalidScoreIterationTerminationCondition() - Constructor for class org.deeplearning4j.earlystopping.termination.InvalidScoreIterationTerminationCondition
-
- InvalidStepException - Exception in org.deeplearning4j.exception
-
Created by agibsonccc on 8/20/14.
- InvalidStepException(String) - Constructor for exception org.deeplearning4j.exception.InvalidStepException
-
Constructs a new exception with the specified detail message.
- InvalidStepException(String, Throwable) - Constructor for exception org.deeplearning4j.exception.InvalidStepException
-
Constructs a new exception with the specified detail message and
cause.
- InvalidStepException(Throwable) - Constructor for exception org.deeplearning4j.exception.InvalidStepException
-
Constructs a new exception with the specified cause and a detail
message of (cause==null ? null : cause.toString()) (which
typically contains the class and detail message of cause).
- InvalidStepException(String, Throwable, boolean, boolean) - Constructor for exception org.deeplearning4j.exception.InvalidStepException
-
Constructs a new exception with the specified detail message,
cause, suppression enabled or disabled, and writable stack
trace enabled or disabled.
- inverse - Variable in class org.deeplearning4j.clustering.strategy.BaseClusteringStrategy
-
- inverseDistanceCalculation() - Method in class org.deeplearning4j.clustering.strategy.BaseClusteringStrategy
-
- inverseDistanceCalculation() - Method in interface org.deeplearning4j.clustering.strategy.ClusteringStrategy
-
- inverseDistanceCalculation() - Method in class org.deeplearning4j.clustering.strategy.FixedClusterCountStrategy
-
- invert() - Method in class com.atilika.kuromoji.buffer.FeatureInfoMap
-
- invertDistanceMetric(boolean) - Method in class org.deeplearning4j.plot.BarnesHutTsne.Builder
-
- InvertedIndex<T extends SequenceElement> - Interface in org.deeplearning4j.text.invertedindex
-
An inverted index for mapping words to documents
and documents to words
- invocationCount - Variable in class org.deeplearning4j.optimize.listeners.EvaluativeListener
-
- InvocationType - Enum in org.deeplearning4j.optimize.api
-
This enum holds options for TrainingListener invocation scheme
- invocationType - Variable in class org.deeplearning4j.optimize.listeners.EvaluativeListener
-
- INVOKE - Static variable in class com.atilika.kuromoji.dict.CharacterDefinitions
-
- invokeListener(Model) - Method in class org.deeplearning4j.optimize.listeners.EvaluativeListener
-
- iou(DetectedObject, DetectedObject) - Static method in class org.deeplearning4j.nn.layers.objdetect.YoloUtils
-
Returns intersection over union (IOU) between o1 and o2.
- IOutputLayer - Interface in org.deeplearning4j.nn.api.layers
-
Interface for output layers (those that calculate gradients with respect to a labels array)
- iris() - Static method in class org.deeplearning4j.datasets.DataSets
-
- iris(int) - Static method in class org.deeplearning4j.datasets.DataSets
-
- IrisDataFetcher - Class in org.deeplearning4j.datasets.fetchers
-
- IrisDataFetcher() - Constructor for class org.deeplearning4j.datasets.fetchers.IrisDataFetcher
-
- IrisDataSetIterator - Class in org.deeplearning4j.datasets.iterator.impl
-
- IrisDataSetIterator(int, int) - Constructor for class org.deeplearning4j.datasets.iterator.impl.IrisDataSetIterator
-
IrisDataSetIterator handles
traversing through the Iris Data Set.
- IrisUtils - Class in org.deeplearning4j.base
-
- isActive() - Method in class org.ansj.domain.NewWord
-
- isAllowEmptyClusters() - Method in interface org.deeplearning4j.clustering.strategy.ClusteringStrategy
-
- isAsianName - Variable in class org.ansj.dic.LearnTool
-
是否开启学习机
- isAttached(StatsStorage) - Method in class org.deeplearning4j.ui.api.UIServer
-
Check whether the specified StatsStorage instance is attached to the UI instance
- isAttached(StatsStorage) - Method in class org.deeplearning4j.ui.play.PlayUIServer
-
- isAutoDiscoveryMode - Variable in class org.deeplearning4j.spark.models.sequencevectors.SparkSequenceVectors
-
- isBalanced(EmnistDataSetIterator.Set) - Static method in class org.deeplearning4j.datasets.iterator.impl.EmnistDataSetIterator
-
Are the labels balanced in the training set (that is: are the number of examples for each label equal?)
- isBeginLabel() - Method in class org.deeplearning4j.text.movingwindow.Window
-
- isBiasParam(Layer, String) - Method in interface org.deeplearning4j.nn.api.ParamInitializer
-
Is the specified parameter a bias?
- isBiasParam(Layer, String) - Method in class org.deeplearning4j.nn.layers.ocnn.OCNNParamInitializer
-
- isBiasParam(Layer, String) - Method in class org.deeplearning4j.nn.params.BatchNormalizationParamInitializer
-
- isBiasParam(Layer, String) - Method in class org.deeplearning4j.nn.params.BidirectionalParamInitializer
-
- isBiasParam(Layer, String) - Method in class org.deeplearning4j.nn.params.ConvolutionParamInitializer
-
- isBiasParam(Layer, String) - Method in class org.deeplearning4j.nn.params.DefaultParamInitializer
-
- isBiasParam(Layer, String) - Method in class org.deeplearning4j.nn.params.DepthwiseConvolutionParamInitializer
-
- isBiasParam(Layer, String) - Method in class org.deeplearning4j.nn.params.EmptyParamInitializer
-
- isBiasParam(Layer, String) - Method in class org.deeplearning4j.nn.params.FrozenLayerParamInitializer
-
- isBiasParam(Layer, String) - Method in class org.deeplearning4j.nn.params.FrozenLayerWithBackpropParamInitializer
-
- isBiasParam(Layer, String) - Method in class org.deeplearning4j.nn.params.GravesBidirectionalLSTMParamInitializer
-
- isBiasParam(Layer, String) - Method in class org.deeplearning4j.nn.params.GravesLSTMParamInitializer
-
- isBiasParam(Layer, String) - Method in class org.deeplearning4j.nn.params.LSTMParamInitializer
-
- isBiasParam(Layer, String) - Method in class org.deeplearning4j.nn.params.SameDiffParamInitializer
-
- isBiasParam(Layer, String) - Method in class org.deeplearning4j.nn.params.SeparableConvolutionParamInitializer
-
- isBiasParam(Layer, String) - Method in class org.deeplearning4j.nn.params.SimpleRnnParamInitializer
-
- isBiasParam(Layer, String) - Method in class org.deeplearning4j.nn.params.VariationalAutoencoderParamInitializer
-
- isBiasParam(Layer, String) - Method in class org.deeplearning4j.nn.params.WrapperLayerParamInitializer
-
- isBlockingMessage() - Method in class org.deeplearning4j.spark.parameterserver.networking.messages.SilentIntroductoryMessage
-
- isCached() - Method in class org.deeplearning4j.datasets.fetchers.CacheableExtractableDataSetFetcher
-
Returns a boolean indicating if the dataset is already cached locally.
- isClosed() - Method in interface org.deeplearning4j.api.storage.StatsStorage
-
- isClosed() - Method in class org.deeplearning4j.ui.storage.InMemoryStatsStorage
-
- isClosed() - Method in class org.deeplearning4j.ui.storage.mapdb.MapDBStatsStorage
-
- isClosed() - Method in class org.deeplearning4j.ui.storage.sqlite.J7FileStatsStorage
-
- isClusteringOptimizationType(ClusteringOptimizationType) - Method in class org.deeplearning4j.clustering.strategy.OptimisationStrategy
-
- isCorrect() - Method in class org.deeplearning4j.clustering.quadtree.QuadTree
-
Returns whether the tree is consistent or not
- isCorrect() - Method in class org.deeplearning4j.clustering.sptree.SpTree
-
Verifies the structure of the tree (does bounds checking on each node)
- isDebug - Variable in class org.deeplearning4j.optimize.solvers.accumulation.EncodedGradientsAccumulator
-
- isDebug - Variable in class org.deeplearning4j.optimize.solvers.accumulation.FancyBlockingQueue
-
- isDone - Variable in class org.deeplearning4j.optimize.solvers.accumulation.EncodedGradientsAccumulator
-
- isDone - Variable in class org.deeplearning4j.optimize.solvers.accumulation.FancyBlockingQueue
-
- isEarlyTerminationHit() - Method in interface org.deeplearning4j.models.embeddings.learning.ElementsLearningAlgorithm
-
- isEarlyTerminationHit() - Method in class org.deeplearning4j.models.embeddings.learning.impl.elements.CBOW
-
- isEarlyTerminationHit() - Method in class org.deeplearning4j.models.embeddings.learning.impl.elements.GloVe
-
Since GloVe is learning representations using elements CoOccurences, all training is done in GloVe class internally, so only first thread will execute learning process,
and the rest of parent threads will just exit learning process
- isEarlyTerminationHit() - Method in class org.deeplearning4j.models.embeddings.learning.impl.elements.SkipGram
-
SkipGram has no reasons for early termination ever.
- isEarlyTerminationHit() - Method in class org.deeplearning4j.models.embeddings.learning.impl.sequence.DBOW
-
DBOW has no reasons for early termination
- isEarlyTerminationHit() - Method in class org.deeplearning4j.models.embeddings.learning.impl.sequence.DM
-
- isEarlyTerminationHit() - Method in interface org.deeplearning4j.models.embeddings.learning.SequenceLearningAlgorithm
-
- isEarlyTerminationHit() - Method in class org.deeplearning4j.spark.models.sequencevectors.learning.elements.BaseSparkLearningAlgorithm
-
- isEarlyTerminationHit() - Method in class org.deeplearning4j.spark.models.sequencevectors.learning.sequence.BaseSparkSequenceLearningAlgorithm
-
- isEmpty() - Method in class com.atilika.kuromoji.trie.PatriciaTrie
-
Predicate indicating whether this trie is empty
- isEmpty() - Method in class org.deeplearning4j.clustering.cluster.Cluster
-
Whether the cluster is empty or not
- isEmpty() - Method in class org.deeplearning4j.models.sequencevectors.sequence.Sequence
-
Checks, if sequence is empty
- isEmpty() - Method in class org.deeplearning4j.optimize.solvers.accumulation.FancyBlockingQueue
-
- isEmpty() - Method in class org.deeplearning4j.parallelism.ConcurrentHashSet
-
Deprecated.
- isEmpty() - Method in class org.deeplearning4j.parallelism.MagicQueue
-
Deprecated.
- isEmpty() - Method in class org.deeplearning4j.util.DiskBasedQueue
-
- isEnabled() - Method in class org.deeplearning4j.ui.module.remote.RemoteReceiverModule
-
- isEndLabel() - Method in class org.deeplearning4j.text.movingwindow.Window
-
- isEnvironmentReady - Variable in class org.deeplearning4j.spark.models.sequencevectors.SparkSequenceVectors
-
- isFirst - Variable in class org.deeplearning4j.optimize.solvers.accumulation.EncodedGradientsAccumulator
-
- isFirst - Variable in class org.deeplearning4j.optimize.solvers.accumulation.FancyBlockingQueue
-
- isFirst - Variable in class org.deeplearning4j.spark.parameterserver.pw.SharedTrainingWrapper
-
- isFirstRun - Variable in class org.deeplearning4j.spark.parameterserver.training.SharedTrainingMaster
-
- isFName(String) - Static method in class org.ansj.recognition.arrimpl.ForeignPersonRecognition
-
- isForeignName - Variable in class org.ansj.dic.LearnTool
-
- isGraphNetwork - Variable in class org.deeplearning4j.spark.api.WorkerConfiguration
-
- isInference() - Method in enum org.deeplearning4j.nn.conf.memory.MemoryType
-
- isInitCalled() - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
-
- isInputPreProcessor() - Method in class org.deeplearning4j.nn.modelimport.keras.KerasLayer
-
Whether this Keras layer maps to a DL4J InputPreProcessor.
- isInputPreProcessor() - Method in class org.deeplearning4j.nn.modelimport.keras.layers.core.KerasFlatten
-
Whether this Keras layer maps to a DL4J InputPreProcessor.
- isInputPreProcessor() - Method in class org.deeplearning4j.nn.modelimport.keras.layers.core.KerasPermute
-
- isInputPreProcessor() - Method in class org.deeplearning4j.nn.modelimport.keras.layers.core.KerasReshape
-
Whether this Keras layer maps to a DL4J InputPreProcessor.
- isInputVertex() - Method in class org.deeplearning4j.nn.graph.vertex.BaseGraphVertex
-
- isInputVertex() - Method in class org.deeplearning4j.nn.graph.vertex.BaseWrapperVertex
-
- isInputVertex() - Method in interface org.deeplearning4j.nn.graph.vertex.GraphVertex
-
Whether the GraphVertex is an input vertex
- isInputVertex() - Method in class org.deeplearning4j.nn.graph.vertex.impl.InputVertex
-
- isInSystemDic(String) - Static method in class org.ansj.library.DATDictionary
-
判断一个词语是否在词典中
- isInverse() - Method in class org.deeplearning4j.clustering.cluster.ClusterSet
-
- isInvert() - Method in class org.deeplearning4j.plot.BarnesHutTsne
-
- isJoinSupported() - Method in class org.deeplearning4j.spark.parameterserver.networking.messages.SilentUpdatesMessage
-
- isKnown() - Method in class com.atilika.kuromoji.TokenBase
-
Predicate indicating whether this token is known (contained in the standard dictionary)
- isLabel - Variable in class org.deeplearning4j.models.sequencevectors.sequence.SequenceElement
-
- isLabel() - Method in class org.deeplearning4j.models.sequencevectors.sequence.SequenceElement
-
Returns whether this element was defined as label, or no
- isLabelEnabled() - Method in interface org.deeplearning4j.models.sequencevectors.graph.walkers.GraphWalker
-
- isLabelEnabled() - Method in class org.deeplearning4j.models.sequencevectors.graph.walkers.impl.NearestVertexWalker
-
- isLabelEnabled() - Method in class org.deeplearning4j.models.sequencevectors.graph.walkers.impl.PopularityWalker
-
- isLabelEnabled() - Method in class org.deeplearning4j.models.sequencevectors.graph.walkers.impl.RandomWalker
-
- isLabelEnabled() - Method in class org.deeplearning4j.models.sequencevectors.graph.walkers.impl.WeightedWalker
-
- isLayer() - Method in class org.deeplearning4j.nn.modelimport.keras.KerasLayer
-
Whether this Keras layer maps to a DL4J Layer.
- isLeaf() - Method in class org.deeplearning4j.clustering.quadtree.QuadTree
-
- isLeaf() - Method in class org.deeplearning4j.clustering.sptree.SpTree
-
- isLeaf() - Method in class org.deeplearning4j.nn.layers.feedforward.autoencoder.recursive.Tree
-
Returns whether the node has any children or not
- isLocked() - Method in class org.deeplearning4j.parallelism.inference.observers.BatchedInferenceObservable
-
- isMinibatch - Variable in class org.deeplearning4j.nn.conf.layers.BatchNormalization.Builder
-
- isMinibatch - Variable in class org.deeplearning4j.nn.conf.layers.BatchNormalization
-
- isMiniBatch() - Method in class org.deeplearning4j.nn.updater.BaseMultiLayerUpdater
-
- isMiniBatch() - Method in class org.deeplearning4j.nn.updater.graph.ComputationGraphUpdater
-
- isMiniBatch() - Method in class org.deeplearning4j.nn.updater.LayerUpdater
-
- isMiniBatch() - Method in class org.deeplearning4j.nn.updater.MultiLayerUpdater
-
- isMQ - Variable in class org.deeplearning4j.parallelism.ParallelWrapper.Builder
-
- isMQ - Variable in class org.deeplearning4j.parallelism.ParallelWrapper
-
- isNameRecognition - Variable in class org.ansj.splitWord.Analysis
-
- isNameRecognition - Static variable in class org.ansj.util.MyStaticValue
-
- isNCDHW - Variable in class org.deeplearning4j.nn.conf.preprocessor.Cnn3DToFeedForwardPreProcessor
-
- isNewWord() - Method in class org.ansj.domain.Term
-
- isNumRecognition - Variable in class org.ansj.splitWord.Analysis
-
- isNumRecognition - Static variable in class org.ansj.util.MyStaticValue
-
- isOptimizationApplicableNow(IterationHistory) - Method in interface org.deeplearning4j.clustering.strategy.ClusteringStrategy
-
- isOptimizationApplicableNow(IterationHistory) - Method in class org.deeplearning4j.clustering.strategy.FixedClusterCountStrategy
-
- isOptimizationApplicableNow(IterationHistory) - Method in class org.deeplearning4j.clustering.strategy.OptimisationStrategy
-
- isOptimizationDefined() - Method in interface org.deeplearning4j.clustering.strategy.ClusteringStrategy
-
- isOptimizationDefined() - Method in class org.deeplearning4j.clustering.strategy.FixedClusterCountStrategy
-
- isOptimizationDefined() - Method in class org.deeplearning4j.clustering.strategy.OptimisationStrategy
-
- isOutputVertex() - Method in class org.deeplearning4j.nn.graph.vertex.BaseWrapperVertex
-
- isOutputVertex() - Method in interface org.deeplearning4j.nn.graph.vertex.GraphVertex
-
Whether the GraphVertex is an output vertex
- isOutputVertex() - Method in class org.deeplearning4j.nn.graph.vertex.impl.InputVertex
-
- isOutputVertex() - Method in class org.deeplearning4j.nn.graph.vertex.impl.LayerVertex
-
- isOutputVertex() - Method in class org.deeplearning4j.nn.graph.vertex.impl.rnn.DuplicateToTimeSeriesVertex
-
- isOutputVertex() - Method in class org.deeplearning4j.nn.graph.vertex.impl.rnn.ReverseTimeSeriesVertex
-
- isParallel - Variable in class org.deeplearning4j.bagofwords.vectorizer.BagOfWordsVectorizer.Builder
-
- isParallel - Variable in class org.deeplearning4j.bagofwords.vectorizer.BaseTextVectorizer
-
- isParallel - Variable in class org.deeplearning4j.bagofwords.vectorizer.TfidfVectorizer.Builder
-
- isPartOfSpeechFeature(int) - Method in class com.atilika.kuromoji.buffer.TokenInfoBuffer
-
- isPreTerminal() - Method in class org.deeplearning4j.nn.layers.feedforward.autoencoder.recursive.Tree
-
Node has one child that is a leaf
- isPretrainLayer() - Method in interface org.deeplearning4j.nn.api.Layer
-
Returns true if the layer can be trained in an unsupervised/pretrain manner (AE, VAE, etc)
- isPretrainLayer() - Method in class org.deeplearning4j.nn.layers.ActivationLayer
-
- isPretrainLayer() - Method in class org.deeplearning4j.nn.layers.BaseOutputLayer
-
- isPretrainLayer() - Method in class org.deeplearning4j.nn.layers.convolution.CnnLossLayer
-
- isPretrainLayer() - Method in class org.deeplearning4j.nn.layers.convolution.ConvolutionLayer
-
- isPretrainLayer() - Method in class org.deeplearning4j.nn.layers.convolution.Cropping1DLayer
-
- isPretrainLayer() - Method in class org.deeplearning4j.nn.layers.convolution.Cropping2DLayer
-
- isPretrainLayer() - Method in class org.deeplearning4j.nn.layers.convolution.Cropping3DLayer
-
- isPretrainLayer() - Method in class org.deeplearning4j.nn.layers.convolution.SpaceToBatch
-
- isPretrainLayer() - Method in class org.deeplearning4j.nn.layers.convolution.SpaceToDepth
-
- isPretrainLayer() - Method in class org.deeplearning4j.nn.layers.convolution.subsampling.Subsampling3DLayer
-
- isPretrainLayer() - Method in class org.deeplearning4j.nn.layers.convolution.subsampling.SubsamplingLayer
-
- isPretrainLayer() - Method in class org.deeplearning4j.nn.layers.convolution.upsampling.Upsampling2D
-
- isPretrainLayer() - Method in class org.deeplearning4j.nn.layers.convolution.upsampling.Upsampling3D
-
- isPretrainLayer() - Method in class org.deeplearning4j.nn.layers.convolution.ZeroPadding1DLayer
-
- isPretrainLayer() - Method in class org.deeplearning4j.nn.layers.convolution.ZeroPadding3DLayer
-
- isPretrainLayer() - Method in class org.deeplearning4j.nn.layers.convolution.ZeroPaddingLayer
-
- isPretrainLayer() - Method in class org.deeplearning4j.nn.layers.DropoutLayer
-
- isPretrainLayer() - Method in class org.deeplearning4j.nn.layers.feedforward.autoencoder.AutoEncoder
-
- isPretrainLayer() - Method in class org.deeplearning4j.nn.layers.feedforward.dense.DenseLayer
-
- isPretrainLayer() - Method in class org.deeplearning4j.nn.layers.feedforward.elementwise.ElementWiseMultiplicationLayer
-
Returns true if the layer can be trained in an unsupervised/pretrain manner (VAE, RBMs etc)
- isPretrainLayer() - Method in class org.deeplearning4j.nn.layers.feedforward.embedding.EmbeddingLayer
-
- isPretrainLayer() - Method in class org.deeplearning4j.nn.layers.feedforward.embedding.EmbeddingSequenceLayer
-
- isPretrainLayer() - Method in class org.deeplearning4j.nn.layers.LossLayer
-
- isPretrainLayer() - Method in class org.deeplearning4j.nn.layers.normalization.BatchNormalization
-
- isPretrainLayer() - Method in class org.deeplearning4j.nn.layers.normalization.LocalResponseNormalization
-
- isPretrainLayer() - Method in class org.deeplearning4j.nn.layers.objdetect.Yolo2OutputLayer
-
- isPretrainLayer() - Method in class org.deeplearning4j.nn.layers.pooling.GlobalPoolingLayer
-
- isPretrainLayer() - Method in class org.deeplearning4j.nn.layers.recurrent.BidirectionalLayer
-
- isPretrainLayer() - Method in class org.deeplearning4j.nn.layers.recurrent.GravesBidirectionalLSTM
-
- isPretrainLayer() - Method in class org.deeplearning4j.nn.layers.recurrent.GravesLSTM
-
- isPretrainLayer() - Method in class org.deeplearning4j.nn.layers.recurrent.LSTM
-
- isPretrainLayer() - Method in class org.deeplearning4j.nn.layers.recurrent.RnnLossLayer
-
- isPretrainLayer() - Method in class org.deeplearning4j.nn.layers.recurrent.SimpleRnn
-
- isPretrainLayer() - Method in class org.deeplearning4j.nn.layers.samediff.SameDiffLayer
-
- isPretrainLayer() - Method in class org.deeplearning4j.nn.layers.util.MaskLayer
-
- isPretrainLayer() - Method in class org.deeplearning4j.nn.layers.variational.VariationalAutoencoder
-
- isPretrainLayer() - Method in class org.deeplearning4j.nn.layers.wrapper.BaseWrapperLayer
-
- isPretrainLayer() - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
-
- isPretrainParam(String) - Method in class org.deeplearning4j.nn.conf.layers.ActivationLayer
-
- isPretrainParam(String) - Method in class org.deeplearning4j.nn.conf.layers.BasePretrainNetwork
-
- isPretrainParam(String) - Method in class org.deeplearning4j.nn.conf.layers.BaseUpsamplingLayer
-
- isPretrainParam(String) - Method in class org.deeplearning4j.nn.conf.layers.BatchNormalization
-
- isPretrainParam(String) - Method in class org.deeplearning4j.nn.conf.layers.DropoutLayer
-
- isPretrainParam(String) - Method in class org.deeplearning4j.nn.conf.layers.FeedForwardLayer
-
- isPretrainParam(String) - Method in class org.deeplearning4j.nn.conf.layers.GlobalPoolingLayer
-
- isPretrainParam(String) - Method in class org.deeplearning4j.nn.conf.layers.Layer
-
Is the specified parameter a layerwise pretraining only parameter?
For example, visible bias params in an autoencoder (or, decoder params in a variational autoencoder) aren't
used during supervised backprop.
Layers (like DenseLayer, etc) with no pretrainable parameters will return false for all (valid) inputs.
- isPretrainParam(String) - Method in class org.deeplearning4j.nn.conf.layers.LocalResponseNormalization
-
- isPretrainParam(String) - Method in class org.deeplearning4j.nn.conf.layers.LossLayer
-
- isPretrainParam(String) - Method in class org.deeplearning4j.nn.conf.layers.misc.FrozenLayer
-
- isPretrainParam(String) - Method in class org.deeplearning4j.nn.conf.layers.misc.FrozenLayerWithBackprop
-
- isPretrainParam(String) - Method in class org.deeplearning4j.nn.conf.layers.NoParamLayer
-
- isPretrainParam(String) - Method in class org.deeplearning4j.nn.conf.layers.objdetect.Yolo2OutputLayer
-
- isPretrainParam(String) - Method in class org.deeplearning4j.nn.conf.layers.recurrent.Bidirectional
-
- isPretrainParam(String) - Method in class org.deeplearning4j.nn.conf.layers.samediff.AbstractSameDiffLayer
-
- isPretrainParam(String) - Method in class org.deeplearning4j.nn.conf.layers.SpaceToBatchLayer
-
- isPretrainParam(String) - Method in class org.deeplearning4j.nn.conf.layers.SpaceToDepthLayer
-
- isPretrainParam(String) - Method in class org.deeplearning4j.nn.conf.layers.Subsampling3DLayer
-
- isPretrainParam(String) - Method in class org.deeplearning4j.nn.conf.layers.SubsamplingLayer
-
- isPretrainParam(String) - Method in class org.deeplearning4j.nn.conf.layers.util.MaskLayer
-
- isPretrainParam(String) - Method in class org.deeplearning4j.nn.conf.layers.util.MaskZeroLayer
-
- isPretrainParam(String) - Method in class org.deeplearning4j.nn.conf.layers.variational.VariationalAutoencoder
-
- isPretrainParam(String) - Method in class org.deeplearning4j.nn.conf.layers.wrapper.BaseWrapperLayer
-
- isPretrainParam(String) - Method in class org.deeplearning4j.nn.conf.layers.ZeroPadding1DLayer
-
- isPretrainParam(String) - Method in class org.deeplearning4j.nn.conf.layers.ZeroPadding3DLayer
-
- isPretrainParam(String) - Method in class org.deeplearning4j.nn.layers.variational.VariationalAutoencoder
-
- isPretrainUpdaterBlock() - Method in class org.deeplearning4j.nn.updater.UpdaterBlock
-
- isQuantifierRecognition - Variable in class org.ansj.splitWord.Analysis
-
- isQuantifierRecognition - Static variable in class org.ansj.util.MyStaticValue
-
- isRealName - Variable in class org.ansj.splitWord.Analysis
-
- isRealName - Static variable in class org.ansj.util.MyStaticValue
-
- isRemoteListenerEnabled() - Method in class org.deeplearning4j.ui.api.UIServer
-
- isRemoteListenerEnabled() - Method in class org.deeplearning4j.ui.play.PlayUIServer
-
- isRuleWord(String) - Static method in class org.ansj.splitWord.analysis.NlpAnalysis
-
判断新词识别出来的词是否可信
- isRunning() - Method in class org.deeplearning4j.parallelism.trainer.DefaultTrainer
-
- isRunning() - Method in interface org.deeplearning4j.parallelism.trainer.Trainer
-
- isSatisfied(IterationHistory) - Method in interface org.deeplearning4j.clustering.condition.ClusteringAlgorithmCondition
-
- isSatisfied(IterationHistory) - Method in class org.deeplearning4j.clustering.condition.ConvergenceCondition
-
- isSatisfied(IterationHistory) - Method in class org.deeplearning4j.clustering.condition.FixedIterationCountCondition
-
- isSatisfied(IterationHistory) - Method in class org.deeplearning4j.clustering.condition.VarianceVariationCondition
-
- isSet(int, K) - Method in interface com.atilika.kuromoji.trie.PatriciaTrie.KeyMapper
-
Tests a bit in a key
- isSet(int, String) - Method in class com.atilika.kuromoji.trie.PatriciaTrie.StringKeyMapper
-
- isSingleLayerUpdater() - Method in class org.deeplearning4j.nn.updater.BaseMultiLayerUpdater
-
- isSingleLayerUpdater() - Method in class org.deeplearning4j.nn.updater.LayerUpdater
-
- isSkipUserDefine - Static variable in class org.ansj.util.MyStaticValue
-
是否用户辞典不加载相同的词
- isSplitOnNakaguro(boolean) - Method in class com.atilika.kuromoji.ipadic.Tokenizer.Builder
-
Predictate that splits unknown words on the middle dot character (U+30FB KATAKANA MIDDLE DOT)
- isStem() - Method in class org.deeplearning4j.models.word2vec.VocabWork
-
- isStopped - Variable in class org.deeplearning4j.parallelism.trainer.DefaultTrainer
-
- isStrategyOfType(ClusteringStrategyType) - Method in class org.deeplearning4j.clustering.strategy.BaseClusteringStrategy
-
- isStrategyOfType(ClusteringStrategyType) - Method in interface org.deeplearning4j.clustering.strategy.ClusteringStrategy
-
- isUseAdaGrad() - Method in class org.deeplearning4j.models.embeddings.inmemory.InMemoryLookupTable
-
- isUseAdaGrad() - Method in class org.deeplearning4j.spark.models.embeddings.glove.GloveParam
-
- isUseAdaGrad() - Method in class org.deeplearning4j.spark.models.embeddings.word2vec.Word2VecParam
-
Deprecated.
- isUseAdaGrad() - Method in class org.deeplearning4j.spark.models.embeddings.word2vec.Word2VecPerformerVoid
-
Deprecated.
- isUser() - Method in class com.atilika.kuromoji.TokenBase
-
Predicate indicating whether this token is included is from the user dictionary
- isValidInboundLayer() - Method in class org.deeplearning4j.nn.modelimport.keras.KerasLayer
-
Indicates whether this layer a valid inbound layer.
- isVertex() - Method in class org.deeplearning4j.nn.modelimport.keras.KerasLayer
-
Whether this Keras layer maps to a DL4J Vertex.
- isWeightParam(Layer, String) - Method in interface org.deeplearning4j.nn.api.ParamInitializer
-
Is the specified parameter a weight?
- isWeightParam(Layer, String) - Method in class org.deeplearning4j.nn.layers.ocnn.OCNNParamInitializer
-
- isWeightParam(Layer, String) - Method in class org.deeplearning4j.nn.params.BatchNormalizationParamInitializer
-
- isWeightParam(Layer, String) - Method in class org.deeplearning4j.nn.params.BidirectionalParamInitializer
-
- isWeightParam(Layer, String) - Method in class org.deeplearning4j.nn.params.ConvolutionParamInitializer
-
- isWeightParam(Layer, String) - Method in class org.deeplearning4j.nn.params.DefaultParamInitializer
-
- isWeightParam(Layer, String) - Method in class org.deeplearning4j.nn.params.DepthwiseConvolutionParamInitializer
-
- isWeightParam(Layer, String) - Method in class org.deeplearning4j.nn.params.EmptyParamInitializer
-
- isWeightParam(Layer, String) - Method in class org.deeplearning4j.nn.params.FrozenLayerParamInitializer
-
- isWeightParam(Layer, String) - Method in class org.deeplearning4j.nn.params.FrozenLayerWithBackpropParamInitializer
-
- isWeightParam(Layer, String) - Method in class org.deeplearning4j.nn.params.GravesBidirectionalLSTMParamInitializer
-
- isWeightParam(Layer, String) - Method in class org.deeplearning4j.nn.params.GravesLSTMParamInitializer
-
- isWeightParam(Layer, String) - Method in class org.deeplearning4j.nn.params.LSTMParamInitializer
-
- isWeightParam(Layer, String) - Method in class org.deeplearning4j.nn.params.SameDiffParamInitializer
-
- isWeightParam(Layer, String) - Method in class org.deeplearning4j.nn.params.SeparableConvolutionParamInitializer
-
- isWeightParam(Layer, String) - Method in class org.deeplearning4j.nn.params.SimpleRnnParamInitializer
-
- isWeightParam(Layer, String) - Method in class org.deeplearning4j.nn.params.VariationalAutoencoderParamInitializer
-
- isWeightParam(Layer, String) - Method in class org.deeplearning4j.nn.params.WrapperLayerParamInitializer
-
- item() - Method in class org.ansj.domain.Term
-
- iter - Variable in class org.deeplearning4j.datasets.iterator.MultipleEpochsIterator
-
Deprecated.
- iter - Variable in class org.deeplearning4j.earlystopping.scorecalc.base.BaseIEvaluationScoreCalculator
-
- iter - Variable in class org.deeplearning4j.spark.iterator.BaseDataSetIterator
-
- iterate(DocumentIterator) - Method in class org.deeplearning4j.bagofwords.vectorizer.Builder
-
Deprecated.
- iterate(SentenceIterator) - Method in class org.deeplearning4j.bagofwords.vectorizer.Builder
-
Deprecated.
- iterate(int, int) - Method in interface org.deeplearning4j.graph.models.embeddings.GraphVectorLookupTable
-
Conduct learning given a pair of vertices (in and out)
- iterate(int, int) - Method in class org.deeplearning4j.graph.models.embeddings.InMemoryGraphLookupTable
-
- iterate(T, T) - Method in class org.deeplearning4j.models.embeddings.inmemory.InMemoryLookupTable
-
Deprecated.
- iterate(T, T) - Method in interface org.deeplearning4j.models.embeddings.WeightLookupTable
-
Deprecated.
- iterate(SequenceIterator<T>) - Method in class org.deeplearning4j.models.glove.AbstractCoOccurrences.Builder
-
- iterate(SequenceIterator<VocabWord>) - Method in class org.deeplearning4j.models.glove.Glove.Builder
-
- iterate(SentenceIterator) - Method in class org.deeplearning4j.models.glove.Glove.Builder
-
- iterate(DocumentIterator) - Method in class org.deeplearning4j.models.glove.Glove.Builder
-
- iterate(SequenceIterator<V>) - Method in class org.deeplearning4j.models.node2vec.Node2Vec.Builder
-
Deprecated.
- iterate(LabelAwareDocumentIterator) - Method in class org.deeplearning4j.models.paragraphvectors.ParagraphVectors.Builder
-
This method used to feed LabelAwareDocumentIterator, that contains training corpus, into ParagraphVectors
- iterate(LabelAwareSentenceIterator) - Method in class org.deeplearning4j.models.paragraphvectors.ParagraphVectors.Builder
-
This method used to feed LabelAwareSentenceIterator, that contains training corpus, into ParagraphVectors
- iterate(LabelAwareIterator) - Method in class org.deeplearning4j.models.paragraphvectors.ParagraphVectors.Builder
-
This method used to feed LabelAwareIterator, that contains training corpus, into ParagraphVectors
- iterate(DocumentIterator) - Method in class org.deeplearning4j.models.paragraphvectors.ParagraphVectors.Builder
-
This method used to feed DocumentIterator, that contains training corpus, into ParagraphVectors
- iterate(SentenceIterator) - Method in class org.deeplearning4j.models.paragraphvectors.ParagraphVectors.Builder
-
This method used to feed SentenceIterator, that contains training corpus, into ParagraphVectors
- iterate(SequenceIterator<VocabWord>) - Method in class org.deeplearning4j.models.paragraphvectors.ParagraphVectors.Builder
-
This method used to feed SequenceIterator, that contains training corpus, into ParagraphVectors
- iterate(SequenceIterator<T>) - Method in class org.deeplearning4j.models.sequencevectors.SequenceVectors.Builder
-
This method defines SequenceIterator to be used for model building
- iterate(DocumentIterator) - Method in class org.deeplearning4j.models.word2vec.Word2Vec.Builder
-
- iterate(SentenceIterator) - Method in class org.deeplearning4j.models.word2vec.Word2Vec.Builder
-
This method used to feed SentenceIterator, that contains training corpus, into ParagraphVectors
- iterate(SequenceIterator<VocabWord>) - Method in class org.deeplearning4j.models.word2vec.Word2Vec.Builder
-
This method used to feed SequenceIterator, that contains training corpus, into ParagraphVectors
- iterate(LabelAwareIterator) - Method in class org.deeplearning4j.models.word2vec.Word2Vec.Builder
-
This method used to feed LabelAwareIterator, that is usually used
- iterateBucket(String) - Method in class org.deeplearning4j.aws.s3.reader.S3Downloader
-
Iterate over individual buckets.
- iterateSample(T, T, AtomicLong, double) - Method in class org.deeplearning4j.models.embeddings.inmemory.InMemoryLookupTable
-
Deprecated.
- iterateSample(T, int[], AtomicLong, double, boolean, int, boolean, INDArray) - Method in class org.deeplearning4j.models.embeddings.learning.impl.elements.CBOW
-
- iterateSample(T, T, AtomicLong, double, boolean, INDArray) - Method in class org.deeplearning4j.models.embeddings.learning.impl.elements.SkipGram
-
- iterateSample(T, T, AtomicLong, double) - Method in interface org.deeplearning4j.models.embeddings.WeightLookupTable
-
Deprecated.
- iterateSample(T, T, double) - Method in class org.deeplearning4j.models.glove.GloveWeightLookupTable
-
Deprecated.
glove iteration
- iterateSample(T, T, AtomicLong, double) - Method in class org.deeplearning4j.models.glove.GloveWeightLookupTable
-
Deprecated.
- iterateSample(VocabWord, VocabWord, double) - Method in class org.deeplearning4j.spark.models.embeddings.word2vec.FirstIterationFunctionAdapter
-
- iterateSample(Word2VecParam, VocabWord, VocabWord, double, List<Triple<Integer, Integer, Integer>>) - Method in class org.deeplearning4j.spark.models.embeddings.word2vec.SentenceBatch
-
Deprecated.
Iterate on the given 2 vocab words
- iterateSample(VocabWord, VocabWord, double) - Method in class org.deeplearning4j.spark.models.embeddings.word2vec.Word2VecPerformer
-
Deprecated.
Iterate on the given 2 vocab words
- iterateSample(VocabWord, VocabWord, double) - Method in class org.deeplearning4j.spark.models.embeddings.word2vec.Word2VecPerformerVoid
-
Deprecated.
Iterate on the given 2 vocab words
- iterateSample(ShallowSequenceElement, int[], AtomicLong, double, boolean, int, boolean, INDArray) - Method in class org.deeplearning4j.spark.models.sequencevectors.learning.elements.SparkCBOW
-
- iterateSample(ShallowSequenceElement, ShallowSequenceElement, AtomicLong, double) - Method in class org.deeplearning4j.spark.models.sequencevectors.learning.elements.SparkSkipGram
-
- iterationCount - Variable in class org.deeplearning4j.nn.conf.ComputationGraphConfiguration
-
- iterationCount - Variable in class org.deeplearning4j.nn.conf.MultiLayerConfiguration
-
- iterationCount - Variable in class org.deeplearning4j.nn.conf.NeuralNetConfiguration
-
- iterationCount - Variable in class org.deeplearning4j.nn.layers.AbstractLayer
-
- iterationCount - Variable in class org.deeplearning4j.nn.layers.variational.VariationalAutoencoder
-
- iterationCount - Variable in class org.deeplearning4j.optimize.listeners.EvaluativeListener
-
- iterationCount - Variable in class org.deeplearning4j.spark.impl.paramavg.ParameterAveragingTrainingMaster
-
- iterationCount() - Method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder
-
- iterationCount(int) - Method in class org.deeplearning4j.ui.stats.sbe.UpdateEncoder
-
- iterationCountGreaterThan(int) - Static method in class org.deeplearning4j.clustering.condition.FixedIterationCountCondition
-
- iterationCountId() - Static method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder
-
- iterationCountMaxValue() - Static method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder
-
- iterationCountMaxValue() - Static method in class org.deeplearning4j.ui.stats.sbe.UpdateEncoder
-
- iterationCountMetaAttribute(MetaAttribute) - Static method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder
-
- iterationCountMinValue() - Static method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder
-
- iterationCountMinValue() - Static method in class org.deeplearning4j.ui.stats.sbe.UpdateEncoder
-
- iterationCountNullValue() - Static method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder
-
- iterationCountNullValue() - Static method in class org.deeplearning4j.ui.stats.sbe.UpdateEncoder
-
- iterationDone(Model, int, int) - Method in class org.deeplearning4j.optimize.api.BaseTrainingListener
-
- iterationDone(Model, int, int) - Method in class org.deeplearning4j.optimize.api.IterationListener
-
Deprecated.
Event listener for each iteration
- iterationDone(Model, int, int) - Method in interface org.deeplearning4j.optimize.api.TrainingListener
-
Event listener for each iteration.
- iterationDone(Model, int, int) - Method in class org.deeplearning4j.optimize.listeners.checkpoint.CheckpointListener
-
- iterationDone(Model, int, int) - Method in class org.deeplearning4j.optimize.listeners.CollectScoresIterationListener
-
- iterationDone(Model, int, int) - Method in class org.deeplearning4j.optimize.listeners.CollectScoresListener
-
- iterationDone(Model, int, int) - Method in class org.deeplearning4j.optimize.listeners.ComposableIterationListener
-
- iterationDone(Model, int, int) - Method in class org.deeplearning4j.optimize.listeners.EvaluativeListener
-
Event listener for each iteration
- iterationDone(Model, int, int) - Method in class org.deeplearning4j.optimize.listeners.ParamAndGradientIterationListener
-
- iterationDone(Model, int, int) - Method in class org.deeplearning4j.optimize.listeners.PerformanceListener
-
- iterationDone(Model, int, int) - Method in class org.deeplearning4j.optimize.listeners.ScoreIterationListener
-
- iterationDone(Model, int, int) - Method in class org.deeplearning4j.optimize.listeners.SleepyTrainingListener
-
- iterationDone(Model, int, int) - Method in class org.deeplearning4j.optimize.listeners.TimeIterationListener
-
- iterationDone(Model, int, int) - Method in class org.deeplearning4j.perf.listener.SystemInfoFilePrintListener
-
- iterationDone(Model, int, int) - Method in class org.deeplearning4j.perf.listener.SystemInfoPrintListener
-
- iterationDone(Model, int, int) - Method in class org.deeplearning4j.ui.stats.BaseStatsListener
-
- iterationDone(Model, int, int) - Method in class org.deeplearning4j.ui.weights.ConvolutionalIterationListener
-
Event listener for each iteration
- IterationHistory - Class in org.deeplearning4j.clustering.iteration
-
- IterationHistory() - Constructor for class org.deeplearning4j.clustering.iteration.IterationHistory
-
- IterationInfo - Class in org.deeplearning4j.clustering.iteration
-
- IterationInfo(int) - Constructor for class org.deeplearning4j.clustering.iteration.IterationInfo
-
- IterationInfo(int, ClusterSetInfo) - Constructor for class org.deeplearning4j.clustering.iteration.IterationInfo
-
- IterationListener - Class in org.deeplearning4j.optimize.api
-
- IterationListener() - Constructor for class org.deeplearning4j.optimize.api.IterationListener
-
Deprecated.
- iterations(int) - Method in class org.deeplearning4j.models.glove.Glove.Builder
-
Ierations and epochs are the same in GloVe implementation.
- iterations(int) - Method in class org.deeplearning4j.models.node2vec.Node2Vec.Builder
-
Deprecated.
- iterations(int) - Method in class org.deeplearning4j.models.paragraphvectors.ParagraphVectors.Builder
-
This method defines number of iterations done for each mini-batch during training
- iterations - Variable in class org.deeplearning4j.models.sequencevectors.SequenceVectors.Builder
-
- iterations(int) - Method in class org.deeplearning4j.models.sequencevectors.SequenceVectors.Builder
-
This method defines how much iterations should be done over batched sequences.
- iterations(int) - Method in class org.deeplearning4j.models.word2vec.Word2Vec.Builder
-
This method defines number of iterations done for each mini-batch during training
- iterations - Variable in class org.deeplearning4j.optimize.solvers.accumulation.EncodingHandler
-
- iterations(int) - Method in class org.deeplearning4j.spark.models.embeddings.word2vec.Word2Vec.Builder
-
This method specifies number of iterations over batch on each node
- ITERATIONS - Static variable in class org.deeplearning4j.spark.models.embeddings.word2vec.Word2VecPerformerVoid
-
Deprecated.
- ITERATIONS - Static variable in class org.deeplearning4j.spark.models.embeddings.word2vec.Word2VecVariables
-
Deprecated.
- iterations(int) - Method in class org.deeplearning4j.spark.models.sequencevectors.SparkSequenceVectors.Builder
-
- iterations(int) - Method in class org.deeplearning4j.spark.models.word2vec.SparkWord2Vec.Builder
-
- iterationsCounter - Variable in class org.deeplearning4j.datasets.iterator.MultipleEpochsIterator
-
Deprecated.
- iterationsCounter - Variable in class org.deeplearning4j.parallelism.ParallelWrapper
-
- IterationTerminationCondition - Interface in org.deeplearning4j.earlystopping.termination
-
Interface for termination conditions to be evaluated once per iteration (i.e., once per minibatch).
- iterationTerminationConditions(IterationTerminationCondition...) - Method in class org.deeplearning4j.earlystopping.EarlyStoppingConfiguration.Builder
-
Termination conditions to be evaluated every iteration (minibatch)
- iterator() - Method in class org.ansj.domain.Result
-
- iterator - Variable in class org.deeplearning4j.bagofwords.vectorizer.BagOfWordsVectorizer.Builder
-
- iterator - Variable in class org.deeplearning4j.bagofwords.vectorizer.BaseTextVectorizer
-
- iterator - Variable in class org.deeplearning4j.bagofwords.vectorizer.TfidfVectorizer.Builder
-
- iterator - Variable in class org.deeplearning4j.datasets.iterator.MultiDataSetWrapperIterator
-
- iterator - Variable in class org.deeplearning4j.datasets.iterator.WorkspacesShieldDataSetIterator
-
- iterator - Variable in class org.deeplearning4j.earlystopping.scorecalc.base.BaseIEvaluationScoreCalculator
-
- iterator - Variable in class org.deeplearning4j.earlystopping.scorecalc.base.BaseScoreCalculator
-
- iterator() - Method in class org.deeplearning4j.models.glove.AbstractCoOccurrences
-
This method returns iterator with elements pairs and their weights.
- iterator - Variable in class org.deeplearning4j.models.sequencevectors.SequenceVectors.Builder
-
- iterator - Variable in class org.deeplearning4j.models.sequencevectors.SequenceVectors
-
- iterator() - Method in class org.deeplearning4j.models.sequencevectors.transformers.impl.GraphTransformer
-
- iterator - Variable in class org.deeplearning4j.models.sequencevectors.transformers.impl.iterables.BasicTransformerIterator
-
- iterator - Variable in class org.deeplearning4j.models.sequencevectors.transformers.impl.SentenceTransformer.Builder
-
- iterator(LabelAwareIterator) - Method in class org.deeplearning4j.models.sequencevectors.transformers.impl.SentenceTransformer.Builder
-
- iterator(SentenceIterator) - Method in class org.deeplearning4j.models.sequencevectors.transformers.impl.SentenceTransformer.Builder
-
- iterator(DocumentIterator) - Method in class org.deeplearning4j.models.sequencevectors.transformers.impl.SentenceTransformer.Builder
-
- iterator - Variable in class org.deeplearning4j.models.sequencevectors.transformers.impl.SentenceTransformer
-
- iterator() - Method in class org.deeplearning4j.models.sequencevectors.transformers.impl.SentenceTransformer
-
- iterator() - Method in class org.deeplearning4j.optimize.solvers.accumulation.FancyBlockingQueue
-
- iterator - Variable in class org.deeplearning4j.parallelism.AsyncIterator
-
- iterator() - Method in class org.deeplearning4j.parallelism.ConcurrentHashSet
-
Deprecated.
- iterator() - Method in class org.deeplearning4j.parallelism.MagicQueue
-
Deprecated.
This method isn't supported
- iterator - Variable in class org.deeplearning4j.spark.parameterserver.iterators.MultiPdsIterator
-
- iterator - Variable in class org.deeplearning4j.spark.parameterserver.iterators.PdsIterator
-
- iterator - Variable in class org.deeplearning4j.spark.parameterserver.iterators.VirtualIterator
-
- iterator() - Method in class org.deeplearning4j.text.sentenceiterator.BasicLineIterator
-
Implentation for Iterable interface.
- iterator() - Method in class org.deeplearning4j.ui.stats.sbe.StaticInfoDecoder.HwDeviceInfoGroupDecoder
-
- iterator() - Method in class org.deeplearning4j.ui.stats.sbe.StaticInfoDecoder.ModelParamNamesDecoder
-
- iterator() - Method in class org.deeplearning4j.ui.stats.sbe.StaticInfoDecoder.SwEnvironmentInfoDecoder
-
- iterator() - Method in class org.deeplearning4j.ui.stats.sbe.StorageMetaDataDecoder.ExtraMetaDataBytesDecoder
-
- iterator() - Method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder.DataSetMetaDataBytesDecoder
-
- iterator() - Method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder.DataSetMetaDataBytesDecoder.MetaDataBytesDecoder
-
- iterator() - Method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder.GcStatsDecoder
-
- iterator() - Method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder.LayerNamesDecoder
-
- iterator() - Method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder.MemoryUseDecoder
-
- iterator() - Method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder.ParamNamesDecoder
-
- iterator() - Method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder.PerformanceDecoder
-
- iterator() - Method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder.PerParameterStatsDecoder.HistogramsDecoder.HistogramCountsDecoder
-
- iterator() - Method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder.PerParameterStatsDecoder.HistogramsDecoder
-
- iterator() - Method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder.PerParameterStatsDecoder
-
- iterator() - Method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder.PerParameterStatsDecoder.SummaryStatDecoder
-
- iterator() - Method in class org.deeplearning4j.util.DiskBasedQueue
-
- IteratorDataSetIterator - Class in org.deeplearning4j.datasets.iterator
-
A DataSetIterator that works on an Iterator, combining and splitting the input DataSet objects as
required to get a consistent batch size.
- IteratorDataSetIterator(Iterator<DataSet>, int) - Constructor for class org.deeplearning4j.datasets.iterator.IteratorDataSetIterator
-
- iteratorDS - Variable in class org.deeplearning4j.spark.parameterserver.pw.SharedTrainingWrapper
-
- iteratorMDS - Variable in class org.deeplearning4j.spark.parameterserver.pw.SharedTrainingWrapper
-
- IteratorMultiDataSetIterator - Class in org.deeplearning4j.datasets.iterator
-
A DataSetIterator that works on an Iterator, combining and splitting the input DataSet objects as
required to get a consistent batch size.
- IteratorMultiDataSetIterator(Iterator<MultiDataSet>, int) - Constructor for class org.deeplearning4j.datasets.iterator.IteratorMultiDataSetIterator
-
- iterators - Variable in class org.deeplearning4j.spark.parameterserver.iterators.VirtualDataSetIterator
-
Basic idea here is simple: this DataSetIterator will take in multiple lazy Iterator,
and will push them is round-robin manner to ParallelWrapper workers
- iterators - Variable in class org.deeplearning4j.spark.parameterserver.iterators.VirtualMultiDataSetIterator
-
- iteratorsDS - Variable in class org.deeplearning4j.spark.parameterserver.pw.SharedTrainingWrapper
-
- iteratorsMDS - Variable in class org.deeplearning4j.spark.parameterserver.pw.SharedTrainingWrapper
-
- IteratorUtils - Class in org.deeplearning4j.spark.datavec.iterator
-
- IteratorUtils() - Constructor for class org.deeplearning4j.spark.datavec.iterator.IteratorUtils
-
- iupdater - Variable in class org.deeplearning4j.nn.conf.layers.BaseLayer.Builder
-
- iUpdater - Variable in class org.deeplearning4j.nn.conf.layers.BaseLayer
-
- iUpdater - Variable in class org.deeplearning4j.nn.conf.NeuralNetConfiguration.Builder
-
- IVertexSequence<T> - Interface in org.deeplearning4j.graph.api
-
Represents a sequence of vertices in a graph.
General-purpose, but can be used to represent a walk on a graph, for example.
- IWeightNoise - Interface in org.deeplearning4j.nn.conf.weightnoise
-
IWeightNoise instances operate on an weight array(s), modifying values at training time or test
time, before they are used.
- iz - Variable in class org.deeplearning4j.nn.layers.recurrent.FwdPassReturn
-
- k(double) - Method in class org.deeplearning4j.nn.conf.layers.LocalResponseNormalization.Builder
-
LRN scaling constant k.
- k - Variable in class org.deeplearning4j.nn.conf.layers.LocalResponseNormalization
-
- K_KEY - Static variable in class org.deeplearning4j.nn.layers.ocnn.OCNNParamInitializer
-
- kafkaBroker - Variable in class org.deeplearning4j.streaming.routes.DL4jServeRouteBuilder
-
- kafkaBrokerList(String) - Method in class org.deeplearning4j.streaming.routes.CamelKafkaRouteBuilder.Builder
-
- KafkaUriBuilder - Class in org.deeplearning4j.streaming.kafka
-
Kafka uri builder
- KafkaUriBuilder() - Constructor for class org.deeplearning4j.streaming.kafka.KafkaUriBuilder
-
- kanjiPenalty(int, int) - Method in class com.atilika.kuromoji.ipadic.Tokenizer.Builder
-
Sets a custom kanji penalty
- KDNode(INDArray) - Constructor for class org.deeplearning4j.clustering.kdtree.KDTree.KDNode
-
- KDTree - Class in org.deeplearning4j.clustering.kdtree
-
KDTree based on: https://github.com/nicky-zs/kdtree-python/blob/master/kdtree.py
- KDTree(int) - Constructor for class org.deeplearning4j.clustering.kdtree.KDTree
-
- KDTree.KDNode - Class in org.deeplearning4j.clustering.kdtree
-
- keepAll() - Method in class org.deeplearning4j.optimize.listeners.checkpoint.CheckpointListener.Builder
-
Keep all model checkpoints - i.e., don't delete any.
- keepLast(int) - Method in class org.deeplearning4j.optimize.listeners.checkpoint.CheckpointListener.Builder
-
Keep only the last N most recent model checkpoint files.
- keepLastAndEvery(int, int) - Method in class org.deeplearning4j.optimize.listeners.checkpoint.CheckpointListener.Builder
-
Keep the last N most recent model checkpoint files, and every M checkpoint files.
For example: suppose you save every 100 iterations, for 2050 iteration, and use keepLastAndEvery(3,5).
- Keras1LayerConfiguration - Class in org.deeplearning4j.nn.modelimport.keras.config
-
All relevant property fields of keras 1.x layers.
- Keras1LayerConfiguration() - Constructor for class org.deeplearning4j.nn.modelimport.keras.config.Keras1LayerConfiguration
-
- Keras2LayerConfiguration - Class in org.deeplearning4j.nn.modelimport.keras.config
-
All relevant property fields of keras 2.x layers.
- Keras2LayerConfiguration() - Constructor for class org.deeplearning4j.nn.modelimport.keras.config.Keras2LayerConfiguration
-
- KerasActivation - Class in org.deeplearning4j.nn.modelimport.keras.layers.core
-
Imports an Activation layer from Keras.
- KerasActivation(Map<String, Object>) - Constructor for class org.deeplearning4j.nn.modelimport.keras.layers.core.KerasActivation
-
Constructor from parsed Keras layer configuration dictionary.
- KerasActivation(Map<String, Object>, boolean) - Constructor for class org.deeplearning4j.nn.modelimport.keras.layers.core.KerasActivation
-
Constructor from parsed Keras layer configuration dictionary.
- KerasActivationUtils - Class in org.deeplearning4j.nn.modelimport.keras.utils
-
Utility functionality for Keras activation functions.
- KerasActivationUtils() - Constructor for class org.deeplearning4j.nn.modelimport.keras.utils.KerasActivationUtils
-
- KerasAlphaDropout - Class in org.deeplearning4j.nn.modelimport.keras.layers.noise
-
Keras wrapper for DL4J dropout layer with AlphaDropout.
- KerasAlphaDropout(Integer) - Constructor for class org.deeplearning4j.nn.modelimport.keras.layers.noise.KerasAlphaDropout
-
Pass-through constructor from KerasLayer
- KerasAlphaDropout(Map<String, Object>) - Constructor for class org.deeplearning4j.nn.modelimport.keras.layers.noise.KerasAlphaDropout
-
Constructor from parsed Keras layer configuration dictionary.
- KerasAlphaDropout(Map<String, Object>, boolean) - Constructor for class org.deeplearning4j.nn.modelimport.keras.layers.noise.KerasAlphaDropout
-
Constructor from parsed Keras layer configuration dictionary.
- KerasAtrousConvolution1D - Class in org.deeplearning4j.nn.modelimport.keras.layers.convolutional
-
Keras 1D atrous / dilated convolution layer.
- KerasAtrousConvolution1D(Integer) - Constructor for class org.deeplearning4j.nn.modelimport.keras.layers.convolutional.KerasAtrousConvolution1D
-
Pass-through constructor from KerasLayer
- KerasAtrousConvolution1D(Map<String, Object>) - Constructor for class org.deeplearning4j.nn.modelimport.keras.layers.convolutional.KerasAtrousConvolution1D
-
Constructor from parsed Keras layer configuration dictionary.
- KerasAtrousConvolution1D(Map<String, Object>, boolean) - Constructor for class org.deeplearning4j.nn.modelimport.keras.layers.convolutional.KerasAtrousConvolution1D
-
Constructor from parsed Keras layer configuration dictionary.
- KerasAtrousConvolution2D - Class in org.deeplearning4j.nn.modelimport.keras.layers.convolutional
-
Keras 1D atrous / dilated convolution layer.
- KerasAtrousConvolution2D(Integer) - Constructor for class org.deeplearning4j.nn.modelimport.keras.layers.convolutional.KerasAtrousConvolution2D
-
Pass-through constructor from KerasLayer
- KerasAtrousConvolution2D(Map<String, Object>) - Constructor for class org.deeplearning4j.nn.modelimport.keras.layers.convolutional.KerasAtrousConvolution2D
-
Constructor from parsed Keras layer configuration dictionary.
- KerasAtrousConvolution2D(Map<String, Object>, boolean) - Constructor for class org.deeplearning4j.nn.modelimport.keras.layers.convolutional.KerasAtrousConvolution2D
-
Constructor from parsed Keras layer configuration dictionary.
- kerasBackend - Variable in class org.deeplearning4j.nn.modelimport.keras.KerasModel
-
- KerasBatchNormalization - Class in org.deeplearning4j.nn.modelimport.keras.layers.normalization
-
Imports a BatchNormalization layer from Keras.
- KerasBatchNormalization(Integer) - Constructor for class org.deeplearning4j.nn.modelimport.keras.layers.normalization.KerasBatchNormalization
-
Pass-through constructor from KerasLayer
- KerasBatchNormalization(Map<String, Object>) - Constructor for class org.deeplearning4j.nn.modelimport.keras.layers.normalization.KerasBatchNormalization
-
Constructor from parsed Keras layer configuration dictionary.
- KerasBatchNormalization(Map<String, Object>, boolean) - Constructor for class org.deeplearning4j.nn.modelimport.keras.layers.normalization.KerasBatchNormalization
-
Constructor from parsed Keras layer configuration dictionary.
- KerasBidirectional - Class in org.deeplearning4j.nn.modelimport.keras.layers.wrappers
-
Builds a DL4J Bidirectional layer from a Keras Bidirectional layer wrapper
- KerasBidirectional(Integer) - Constructor for class org.deeplearning4j.nn.modelimport.keras.layers.wrappers.KerasBidirectional
-
Pass-through constructor from KerasLayer
- KerasBidirectional(Map<String, Object>) - Constructor for class org.deeplearning4j.nn.modelimport.keras.layers.wrappers.KerasBidirectional
-
Constructor from parsed Keras layer configuration dictionary.
- KerasBidirectional(Map<String, Object>, boolean) - Constructor for class org.deeplearning4j.nn.modelimport.keras.layers.wrappers.KerasBidirectional
-
Constructor from parsed Keras layer configuration dictionary.
- KerasConstraintUtils - Class in org.deeplearning4j.nn.modelimport.keras.utils
-
Utility functionality for keras constraints.
- KerasConstraintUtils() - Constructor for class org.deeplearning4j.nn.modelimport.keras.utils.KerasConstraintUtils
-
- KerasConvolution - Class in org.deeplearning4j.nn.modelimport.keras.layers.convolutional
-
Keras Convolution base layer
- KerasConvolution(Map<String, Object>) - Constructor for class org.deeplearning4j.nn.modelimport.keras.layers.convolutional.KerasConvolution
-
Constructor from parsed Keras layer configuration dictionary.
- KerasConvolution1D - Class in org.deeplearning4j.nn.modelimport.keras.layers.convolutional
-
Imports a 1D Convolution layer from Keras.
- KerasConvolution1D(Integer) - Constructor for class org.deeplearning4j.nn.modelimport.keras.layers.convolutional.KerasConvolution1D
-
Pass-through constructor from KerasLayer
- KerasConvolution1D(Map<String, Object>) - Constructor for class org.deeplearning4j.nn.modelimport.keras.layers.convolutional.KerasConvolution1D
-
Constructor from parsed Keras layer configuration dictionary.
- KerasConvolution1D(Map<String, Object>, boolean) - Constructor for class org.deeplearning4j.nn.modelimport.keras.layers.convolutional.KerasConvolution1D
-
Constructor from parsed Keras layer configuration dictionary.
- KerasConvolution2D - Class in org.deeplearning4j.nn.modelimport.keras.layers.convolutional
-
Imports a 2D Convolution layer from Keras.
- KerasConvolution2D(Integer) - Constructor for class org.deeplearning4j.nn.modelimport.keras.layers.convolutional.KerasConvolution2D
-
Pass-through constructor from KerasLayer
- KerasConvolution2D(Map<String, Object>) - Constructor for class org.deeplearning4j.nn.modelimport.keras.layers.convolutional.KerasConvolution2D
-
Constructor from parsed Keras layer configuration dictionary.
- KerasConvolution2D(Map<String, Object>, boolean) - Constructor for class org.deeplearning4j.nn.modelimport.keras.layers.convolutional.KerasConvolution2D
-
Constructor from parsed Keras layer configuration dictionary.
- KerasConvolution3D - Class in org.deeplearning4j.nn.modelimport.keras.layers.convolutional
-
Imports a 3D Convolution layer from Keras.
- KerasConvolution3D(Integer) - Constructor for class org.deeplearning4j.nn.modelimport.keras.layers.convolutional.KerasConvolution3D
-
Pass-through constructor from KerasLayer
- KerasConvolution3D(Map<String, Object>) - Constructor for class org.deeplearning4j.nn.modelimport.keras.layers.convolutional.KerasConvolution3D
-
Constructor from parsed Keras layer configuration dictionary.
- KerasConvolution3D(Map<String, Object>, boolean) - Constructor for class org.deeplearning4j.nn.modelimport.keras.layers.convolutional.KerasConvolution3D
-
Constructor from parsed Keras layer configuration dictionary.
- KerasConvolutionUtils - Class in org.deeplearning4j.nn.modelimport.keras.layers.convolutional
-
Utility functionality for Keras convolution layers.
- KerasConvolutionUtils() - Constructor for class org.deeplearning4j.nn.modelimport.keras.layers.convolutional.KerasConvolutionUtils
-
- KerasCropping1D - Class in org.deeplearning4j.nn.modelimport.keras.layers.convolutional
-
Imports a Keras Cropping 1D layer.
- KerasCropping1D(Map<String, Object>) - Constructor for class org.deeplearning4j.nn.modelimport.keras.layers.convolutional.KerasCropping1D
-
Constructor from parsed Keras layer configuration dictionary.
- KerasCropping1D(Map<String, Object>, boolean) - Constructor for class org.deeplearning4j.nn.modelimport.keras.layers.convolutional.KerasCropping1D
-
Constructor from parsed Keras layer configuration dictionary.
- KerasCropping2D - Class in org.deeplearning4j.nn.modelimport.keras.layers.convolutional
-
Imports a Keras Cropping 2D layer.
- KerasCropping2D(Map<String, Object>) - Constructor for class org.deeplearning4j.nn.modelimport.keras.layers.convolutional.KerasCropping2D
-
Constructor from parsed Keras layer configuration dictionary.
- KerasCropping2D(Map<String, Object>, boolean) - Constructor for class org.deeplearning4j.nn.modelimport.keras.layers.convolutional.KerasCropping2D
-
Constructor from parsed Keras layer configuration dictionary.
- KerasCropping3D - Class in org.deeplearning4j.nn.modelimport.keras.layers.convolutional
-
Imports a Keras Cropping 3D layer.
- KerasCropping3D(Map<String, Object>) - Constructor for class org.deeplearning4j.nn.modelimport.keras.layers.convolutional.KerasCropping3D
-
Constructor from parsed Keras layer configuration dictionary.
- KerasCropping3D(Map<String, Object>, boolean) - Constructor for class org.deeplearning4j.nn.modelimport.keras.layers.convolutional.KerasCropping3D
-
Constructor from parsed Keras layer configuration dictionary.
- KerasDeconvolution2D - Class in org.deeplearning4j.nn.modelimport.keras.layers.convolutional
-
Imports a 2D Deconvolution layer from Keras.
- KerasDeconvolution2D(Integer) - Constructor for class org.deeplearning4j.nn.modelimport.keras.layers.convolutional.KerasDeconvolution2D
-
Pass-through constructor from KerasLayer
- KerasDeconvolution2D(Map<String, Object>) - Constructor for class org.deeplearning4j.nn.modelimport.keras.layers.convolutional.KerasDeconvolution2D
-
Constructor from parsed Keras layer configuration dictionary.
- KerasDeconvolution2D(Map<String, Object>, boolean) - Constructor for class org.deeplearning4j.nn.modelimport.keras.layers.convolutional.KerasDeconvolution2D
-
Constructor from parsed Keras layer configuration dictionary.
- KerasDense - Class in org.deeplearning4j.nn.modelimport.keras.layers.core
-
Imports a Dense layer from Keras.
- KerasDense(Integer) - Constructor for class org.deeplearning4j.nn.modelimport.keras.layers.core.KerasDense
-
Pass-through constructor from KerasLayer
- KerasDense(Map<String, Object>) - Constructor for class org.deeplearning4j.nn.modelimport.keras.layers.core.KerasDense
-
Constructor from parsed Keras layer configuration dictionary.
- KerasDense(Map<String, Object>, boolean) - Constructor for class org.deeplearning4j.nn.modelimport.keras.layers.core.KerasDense
-
Constructor from parsed Keras layer configuration dictionary.
- KerasDepthwiseConvolution2D - Class in org.deeplearning4j.nn.modelimport.keras.layers.convolutional
-
Keras depth-wise convolution 2D layer support
- KerasDepthwiseConvolution2D(Integer) - Constructor for class org.deeplearning4j.nn.modelimport.keras.layers.convolutional.KerasDepthwiseConvolution2D
-
Pass-through constructor from KerasLayer
- KerasDepthwiseConvolution2D(Map<String, Object>) - Constructor for class org.deeplearning4j.nn.modelimport.keras.layers.convolutional.KerasDepthwiseConvolution2D
-
Constructor from parsed Keras layer configuration dictionary.
- KerasDepthwiseConvolution2D(Map<String, Object>, Map<String, ? extends KerasLayer>) - Constructor for class org.deeplearning4j.nn.modelimport.keras.layers.convolutional.KerasDepthwiseConvolution2D
-
Constructor from parsed Keras layer configuration dictionary.
- KerasDepthwiseConvolution2D(Map<String, Object>, Map<String, ? extends KerasLayer>, boolean) - Constructor for class org.deeplearning4j.nn.modelimport.keras.layers.convolutional.KerasDepthwiseConvolution2D
-
Constructor from parsed Keras layer configuration dictionary.
- KerasDepthwiseConvolution2D(Map<String, Object>, Map<String, ? extends KerasLayer>, List<String>, boolean) - Constructor for class org.deeplearning4j.nn.modelimport.keras.layers.convolutional.KerasDepthwiseConvolution2D
-
Constructor from parsed Keras layer configuration dictionary.
- KerasDropout - Class in org.deeplearning4j.nn.modelimport.keras.layers.core
-
Imports a Dropout layer from Keras.
- KerasDropout(Map<String, Object>) - Constructor for class org.deeplearning4j.nn.modelimport.keras.layers.core.KerasDropout
-
Constructor from parsed Keras layer configuration dictionary.
- KerasDropout(Map<String, Object>, boolean) - Constructor for class org.deeplearning4j.nn.modelimport.keras.layers.core.KerasDropout
-
Constructor from parsed Keras layer configuration dictionary.
- KerasEmbedding - Class in org.deeplearning4j.nn.modelimport.keras.layers.embeddings
-
Imports an Embedding layer from Keras.
- KerasEmbedding() - Constructor for class org.deeplearning4j.nn.modelimport.keras.layers.embeddings.KerasEmbedding
-
Pass through constructor for unit tests
- KerasEmbedding(Map<String, Object>) - Constructor for class org.deeplearning4j.nn.modelimport.keras.layers.embeddings.KerasEmbedding
-
Constructor from parsed Keras layer configuration dictionary.
- KerasEmbedding(Map<String, Object>, boolean) - Constructor for class org.deeplearning4j.nn.modelimport.keras.layers.embeddings.KerasEmbedding
-
Constructor from parsed Keras layer configuration dictionary.
- KerasFlatten - Class in org.deeplearning4j.nn.modelimport.keras.layers.core
-
Imports a Keras Flatten layer as a DL4J {Cnn,Rnn}ToFeedForwardInputPreProcessor.
- KerasFlatten(Map<String, Object>) - Constructor for class org.deeplearning4j.nn.modelimport.keras.layers.core.KerasFlatten
-
Constructor from parsed Keras layer configuration dictionary.
- KerasFlatten(Map<String, Object>, boolean) - Constructor for class org.deeplearning4j.nn.modelimport.keras.layers.core.KerasFlatten
-
Constructor from parsed Keras layer configuration dictionary.
- KerasFlattenRnnPreprocessor - Class in org.deeplearning4j.nn.modelimport.keras.preprocessors
-
Preprocessor to flatten input of RNN type
- KerasFlattenRnnPreprocessor(int, int) - Constructor for class org.deeplearning4j.nn.modelimport.keras.preprocessors.KerasFlattenRnnPreprocessor
-
- KerasGaussianDropout - Class in org.deeplearning4j.nn.modelimport.keras.layers.noise
-
- KerasGaussianDropout(Integer) - Constructor for class org.deeplearning4j.nn.modelimport.keras.layers.noise.KerasGaussianDropout
-
Pass-through constructor from KerasLayer
- KerasGaussianDropout(Map<String, Object>) - Constructor for class org.deeplearning4j.nn.modelimport.keras.layers.noise.KerasGaussianDropout
-
Constructor from parsed Keras layer configuration dictionary.
- KerasGaussianDropout(Map<String, Object>, boolean) - Constructor for class org.deeplearning4j.nn.modelimport.keras.layers.noise.KerasGaussianDropout
-
Constructor from parsed Keras layer configuration dictionary.
- KerasGaussianNoise - Class in org.deeplearning4j.nn.modelimport.keras.layers.noise
-
- KerasGaussianNoise(Integer) - Constructor for class org.deeplearning4j.nn.modelimport.keras.layers.noise.KerasGaussianNoise
-
Pass-through constructor from KerasLayer
- KerasGaussianNoise(Map<String, Object>) - Constructor for class org.deeplearning4j.nn.modelimport.keras.layers.noise.KerasGaussianNoise
-
Constructor from parsed Keras layer configuration dictionary.
- KerasGaussianNoise(Map<String, Object>, boolean) - Constructor for class org.deeplearning4j.nn.modelimport.keras.layers.noise.KerasGaussianNoise
-
Constructor from parsed Keras layer configuration dictionary.
- KerasGlobalPooling - Class in org.deeplearning4j.nn.modelimport.keras.layers.pooling
-
Imports a Keras Pooling layer as a DL4J Subsampling layer.
- KerasGlobalPooling(Map<String, Object>) - Constructor for class org.deeplearning4j.nn.modelimport.keras.layers.pooling.KerasGlobalPooling
-
Constructor from parsed Keras layer configuration dictionary.
- KerasGlobalPooling(Map<String, Object>, boolean) - Constructor for class org.deeplearning4j.nn.modelimport.keras.layers.pooling.KerasGlobalPooling
-
Constructor from parsed Keras layer configuration dictionary.
- KerasInitilizationUtils - Class in org.deeplearning4j.nn.modelimport.keras.utils
-
Utility functionality for Keras weight initializers
- KerasInitilizationUtils() - Constructor for class org.deeplearning4j.nn.modelimport.keras.utils.KerasInitilizationUtils
-
- KerasInput - Class in org.deeplearning4j.nn.modelimport.keras.layers
-
Imports an Input layer from Keras.
- KerasInput(Map<String, Object>) - Constructor for class org.deeplearning4j.nn.modelimport.keras.layers.KerasInput
-
Constructor from parsed Keras layer configuration dictionary.
- KerasInput(Map<String, Object>, boolean) - Constructor for class org.deeplearning4j.nn.modelimport.keras.layers.KerasInput
-
Constructor from parsed Keras layer configuration dictionary.
- KerasInput(String, int[]) - Constructor for class org.deeplearning4j.nn.modelimport.keras.layers.KerasInput
-
Constructor from layer name and input shape.
- KerasInput(String, int[], boolean) - Constructor for class org.deeplearning4j.nn.modelimport.keras.layers.KerasInput
-
Constructor from layer name and input shape.
- KerasLayer - Class in org.deeplearning4j.nn.modelimport.keras
-
Build Layer from Keras layer configuration.
- KerasLayer(Integer) - Constructor for class org.deeplearning4j.nn.modelimport.keras.KerasLayer
-
Constructor with Keras version only.
- KerasLayer() - Constructor for class org.deeplearning4j.nn.modelimport.keras.KerasLayer
-
Default constructor.
- KerasLayer(Map<String, Object>) - Constructor for class org.deeplearning4j.nn.modelimport.keras.KerasLayer
-
Constructor.
- KerasLayer(Map<String, Object>, boolean) - Constructor for class org.deeplearning4j.nn.modelimport.keras.KerasLayer
-
Constructor.
- KerasLayer.DimOrder - Enum in org.deeplearning4j.nn.modelimport.keras
-
- KerasLayerConfiguration - Class in org.deeplearning4j.nn.modelimport.keras.config
-
All relevant property fields of keras layers.
- KerasLayerConfiguration() - Constructor for class org.deeplearning4j.nn.modelimport.keras.config.KerasLayerConfiguration
-
- KerasLayerConfigurationFactory - Class in org.deeplearning4j.nn.modelimport.keras.config
-
- KerasLayerConfigurationFactory() - Constructor for class org.deeplearning4j.nn.modelimport.keras.config.KerasLayerConfigurationFactory
-
- KerasLayerUtils - Class in org.deeplearning4j.nn.modelimport.keras.utils
-
Utility functionality to import keras models
- KerasLayerUtils() - Constructor for class org.deeplearning4j.nn.modelimport.keras.utils.KerasLayerUtils
-
- KerasLeakyReLU - Class in org.deeplearning4j.nn.modelimport.keras.layers.advanced.activations
-
Imports LeakyReLU layer from Keras
- KerasLeakyReLU(Map<String, Object>) - Constructor for class org.deeplearning4j.nn.modelimport.keras.layers.advanced.activations.KerasLeakyReLU
-
Constructor from parsed Keras layer configuration dictionary.
- KerasLeakyReLU(Map<String, Object>, boolean) - Constructor for class org.deeplearning4j.nn.modelimport.keras.layers.advanced.activations.KerasLeakyReLU
-
Constructor from parsed Keras layer configuration dictionary.
- KerasLoss - Class in org.deeplearning4j.nn.modelimport.keras.layers
-
Builds a DL4J LossLayer from a Keras training loss function.
- KerasLoss(String, String, String) - Constructor for class org.deeplearning4j.nn.modelimport.keras.layers.KerasLoss
-
Constructor from layer name and input shape.
- KerasLoss(String, String, String, boolean) - Constructor for class org.deeplearning4j.nn.modelimport.keras.layers.KerasLoss
-
Constructor from layer name and input shape.
- KerasLossUtils - Class in org.deeplearning4j.nn.modelimport.keras.utils
-
Utility functionality for keras loss functions
- KerasLossUtils() - Constructor for class org.deeplearning4j.nn.modelimport.keras.utils.KerasLossUtils
-
- KerasLRN - Class in org.deeplearning4j.nn.modelimport.keras.layers.custom
-
Keras does not have an official LRN layer.
- KerasLRN(Map<String, Object>) - Constructor for class org.deeplearning4j.nn.modelimport.keras.layers.custom.KerasLRN
-
Constructor from parsed Keras layer configuration dictionary.
- KerasLRN(Map<String, Object>, boolean) - Constructor for class org.deeplearning4j.nn.modelimport.keras.layers.custom.KerasLRN
-
Constructor from parsed Keras layer configuration dictionary.
- KerasLstm - Class in org.deeplearning4j.nn.modelimport.keras.layers.recurrent
-
Imports a Keras LSTM layer as a DL4J LSTM layer.
- KerasLstm(Integer) - Constructor for class org.deeplearning4j.nn.modelimport.keras.layers.recurrent.KerasLstm
-
Pass-through constructor from KerasLayer
- KerasLstm(Map<String, Object>) - Constructor for class org.deeplearning4j.nn.modelimport.keras.layers.recurrent.KerasLstm
-
Constructor from parsed Keras layer configuration dictionary.
- KerasLstm(Map<String, Object>, boolean) - Constructor for class org.deeplearning4j.nn.modelimport.keras.layers.recurrent.KerasLstm
-
Constructor from parsed Keras layer configuration dictionary.
- KerasLstm(Map<String, Object>, Map<String, ? extends KerasLayer>) - Constructor for class org.deeplearning4j.nn.modelimport.keras.layers.recurrent.KerasLstm
-
Constructor from parsed Keras layer configuration dictionary.
- KerasLstm(Map<String, Object>, boolean, Map<String, ? extends KerasLayer>) - Constructor for class org.deeplearning4j.nn.modelimport.keras.layers.recurrent.KerasLstm
-
Constructor from parsed Keras layer configuration dictionary.
- kerasMajorVersion - Variable in class org.deeplearning4j.nn.modelimport.keras.KerasLayer
-
- kerasMajorVersion - Variable in class org.deeplearning4j.nn.modelimport.keras.KerasModel
-
- KerasMerge - Class in org.deeplearning4j.nn.modelimport.keras.layers.core
-
Imports a Keras Merge layer as a DL4J Merge (graph) vertex.
- KerasMerge(Integer) - Constructor for class org.deeplearning4j.nn.modelimport.keras.layers.core.KerasMerge
-
Pass-through constructor from KerasLayer
- KerasMerge(Map<String, Object>) - Constructor for class org.deeplearning4j.nn.modelimport.keras.layers.core.KerasMerge
-
Constructor from parsed Keras layer configuration dictionary.
- KerasMerge(Map<String, Object>, ElementWiseVertex.Op, boolean) - Constructor for class org.deeplearning4j.nn.modelimport.keras.layers.core.KerasMerge
-
Constructor from parsed Keras layer configuration dictionary and merge mode passed in.
- KerasMerge(Map<String, Object>, boolean) - Constructor for class org.deeplearning4j.nn.modelimport.keras.layers.core.KerasMerge
-
Constructor from parsed Keras layer configuration dictionary.
- KerasModel - Class in org.deeplearning4j.nn.modelimport.keras
-
Build ComputationGraph from Keras (Functional API) Model or
Sequential model configuration.
- KerasModel() - Constructor for class org.deeplearning4j.nn.modelimport.keras.KerasModel
-
- KerasModel(KerasModelBuilder) - Constructor for class org.deeplearning4j.nn.modelimport.keras.KerasModel
-
(Recommended) Builder-pattern constructor for (Functional API) Model.
- KerasModel(String, String, Hdf5Archive, String, String, Hdf5Archive, boolean, int[]) - Constructor for class org.deeplearning4j.nn.modelimport.keras.KerasModel
-
(Not recommended) Constructor for (Functional API) Model from model configuration
(JSON or YAML), training configuration (JSON), weights, and "training mode"
boolean indicator.
- KerasModelBuilder - Class in org.deeplearning4j.nn.modelimport.keras.utils
-
- KerasModelBuilder(KerasModelConfiguration) - Constructor for class org.deeplearning4j.nn.modelimport.keras.utils.KerasModelBuilder
-
- KerasModelConfiguration - Class in org.deeplearning4j.nn.modelimport.keras.config
-
Basic properties and field names of serialised Keras models.
- KerasModelConfiguration() - Constructor for class org.deeplearning4j.nn.modelimport.keras.config.KerasModelConfiguration
-
- KerasModelImport - Class in org.deeplearning4j.nn.modelimport.keras
-
Reads stored Keras configurations and weights from one of two archives:
either (1) a single HDF5 file storing model and training JSON configurations
and weights or (2) separate text file storing model JSON configuration and
HDF5 file storing weights.
- KerasModelImport() - Constructor for class org.deeplearning4j.nn.modelimport.keras.KerasModelImport
-
- KerasModelUtils - Class in org.deeplearning4j.nn.modelimport.keras.utils
-
Utility functionality to import keras models
- KerasModelUtils() - Constructor for class org.deeplearning4j.nn.modelimport.keras.utils.KerasModelUtils
-
- KerasPermute - Class in org.deeplearning4j.nn.modelimport.keras.layers.core
-
Imports Permute layer from Keras
- KerasPermute(Map<String, Object>) - Constructor for class org.deeplearning4j.nn.modelimport.keras.layers.core.KerasPermute
-
Constructor from parsed Keras layer configuration dictionary.
- KerasPermute(Map<String, Object>, boolean) - Constructor for class org.deeplearning4j.nn.modelimport.keras.layers.core.KerasPermute
-
Constructor from parsed Keras layer configuration dictionary.
- KerasPoolHelper - Class in org.deeplearning4j.nn.modelimport.keras.layers.custom
-
Custom PoolHelper layer developed for importing GoogLeNet.
- KerasPoolHelper(Map<String, Object>) - Constructor for class org.deeplearning4j.nn.modelimport.keras.layers.custom.KerasPoolHelper
-
Constructor from parsed Keras layer configuration dictionary.
- KerasPoolHelper(Map<String, Object>, boolean) - Constructor for class org.deeplearning4j.nn.modelimport.keras.layers.custom.KerasPoolHelper
-
Constructor from parsed Keras layer configuration dictionary.
- KerasPooling1D - Class in org.deeplearning4j.nn.modelimport.keras.layers.pooling
-
Imports a Keras 1D Pooling layer as a DL4J Subsampling layer.
- KerasPooling1D(Map<String, Object>) - Constructor for class org.deeplearning4j.nn.modelimport.keras.layers.pooling.KerasPooling1D
-
Constructor from parsed Keras layer configuration dictionary.
- KerasPooling1D(Map<String, Object>, boolean) - Constructor for class org.deeplearning4j.nn.modelimport.keras.layers.pooling.KerasPooling1D
-
Constructor from parsed Keras layer configuration dictionary.
- KerasPooling2D - Class in org.deeplearning4j.nn.modelimport.keras.layers.pooling
-
Imports a Keras 2D Pooling layer as a DL4J Subsampling layer.
- KerasPooling2D(Map<String, Object>) - Constructor for class org.deeplearning4j.nn.modelimport.keras.layers.pooling.KerasPooling2D
-
Constructor from parsed Keras layer configuration dictionary.
- KerasPooling2D(Map<String, Object>, boolean) - Constructor for class org.deeplearning4j.nn.modelimport.keras.layers.pooling.KerasPooling2D
-
Constructor from parsed Keras layer configuration dictionary.
- KerasPooling3D - Class in org.deeplearning4j.nn.modelimport.keras.layers.pooling
-
Imports a Keras 3D Pooling layer as a DL4J Subsampling3D layer.
- KerasPooling3D(Map<String, Object>) - Constructor for class org.deeplearning4j.nn.modelimport.keras.layers.pooling.KerasPooling3D
-
Constructor from parsed Keras layer configuration dictionary.
- KerasPooling3D(Map<String, Object>, boolean) - Constructor for class org.deeplearning4j.nn.modelimport.keras.layers.pooling.KerasPooling3D
-
Constructor from parsed Keras layer configuration dictionary.
- KerasPoolingUtils - Class in org.deeplearning4j.nn.modelimport.keras.layers.pooling
-
Utility functionality for Keras pooling layers.
- KerasPoolingUtils() - Constructor for class org.deeplearning4j.nn.modelimport.keras.layers.pooling.KerasPoolingUtils
-
- KerasRegularizerUtils - Class in org.deeplearning4j.nn.modelimport.keras.utils
-
- KerasRegularizerUtils() - Constructor for class org.deeplearning4j.nn.modelimport.keras.utils.KerasRegularizerUtils
-
- KerasReshape - Class in org.deeplearning4j.nn.modelimport.keras.layers.core
-
Imports Reshape layer from Keras
- KerasReshape(Map<String, Object>) - Constructor for class org.deeplearning4j.nn.modelimport.keras.layers.core.KerasReshape
-
Constructor from parsed Keras layer configuration dictionary.
- KerasReshape(Map<String, Object>, boolean) - Constructor for class org.deeplearning4j.nn.modelimport.keras.layers.core.KerasReshape
-
Constructor from parsed Keras layer configuration dictionary.
- KerasRnnUtils - Class in org.deeplearning4j.nn.modelimport.keras.layers.recurrent
-
Utility functions for Keras RNN layers
- KerasRnnUtils() - Constructor for class org.deeplearning4j.nn.modelimport.keras.layers.recurrent.KerasRnnUtils
-
- KerasSeparableConvolution2D - Class in org.deeplearning4j.nn.modelimport.keras.layers.convolutional
-
Keras separable convolution 2D layer support
- KerasSeparableConvolution2D(Integer) - Constructor for class org.deeplearning4j.nn.modelimport.keras.layers.convolutional.KerasSeparableConvolution2D
-
Pass-through constructor from KerasLayer
- KerasSeparableConvolution2D(Map<String, Object>) - Constructor for class org.deeplearning4j.nn.modelimport.keras.layers.convolutional.KerasSeparableConvolution2D
-
Constructor from parsed Keras layer configuration dictionary.
- KerasSeparableConvolution2D(Map<String, Object>, boolean) - Constructor for class org.deeplearning4j.nn.modelimport.keras.layers.convolutional.KerasSeparableConvolution2D
-
Constructor from parsed Keras layer configuration dictionary.
- KerasSequentialModel - Class in org.deeplearning4j.nn.modelimport.keras
-
Build DL4J MultiLayerNetwork model from Keras Sequential
model configuration.
- KerasSequentialModel(KerasModelBuilder) - Constructor for class org.deeplearning4j.nn.modelimport.keras.KerasSequentialModel
-
(Recommended) Builder-pattern constructor for Sequential model.
- KerasSequentialModel(String, String, Hdf5Archive, String, String, Hdf5Archive, boolean, int[]) - Constructor for class org.deeplearning4j.nn.modelimport.keras.KerasSequentialModel
-
(Not recommended) Constructor for Sequential model from model configuration
(JSON or YAML), training configuration (JSON), weights, and "training mode"
boolean indicator.
- KerasSequentialModel() - Constructor for class org.deeplearning4j.nn.modelimport.keras.KerasSequentialModel
-
- KerasSimpleRnn - Class in org.deeplearning4j.nn.modelimport.keras.layers.recurrent
-
Imports a Keras SimpleRNN layer as a DL4J SimpleRnn layer.
- KerasSimpleRnn(Integer) - Constructor for class org.deeplearning4j.nn.modelimport.keras.layers.recurrent.KerasSimpleRnn
-
Pass-through constructor from KerasLayer
- KerasSimpleRnn(Map<String, Object>) - Constructor for class org.deeplearning4j.nn.modelimport.keras.layers.recurrent.KerasSimpleRnn
-
Constructor from parsed Keras layer configuration dictionary.
- KerasSimpleRnn(Map<String, Object>, boolean) - Constructor for class org.deeplearning4j.nn.modelimport.keras.layers.recurrent.KerasSimpleRnn
-
Constructor from parsed Keras layer configuration dictionary.
- KerasSpaceToDepth - Class in org.deeplearning4j.nn.modelimport.keras.layers.convolutional
-
- KerasSpaceToDepth(Map<String, Object>) - Constructor for class org.deeplearning4j.nn.modelimport.keras.layers.convolutional.KerasSpaceToDepth
-
Constructor from parsed Keras layer configuration dictionary.
- KerasSpaceToDepth(Map<String, Object>, boolean) - Constructor for class org.deeplearning4j.nn.modelimport.keras.layers.convolutional.KerasSpaceToDepth
-
Constructor from parsed Keras layer configuration dictionary.
- KerasSpatialDropout - Class in org.deeplearning4j.nn.modelimport.keras.layers.core
-
Keras wrapper for DL4J dropout layer with SpatialDropout, works 1D-3D.
- KerasSpatialDropout(Integer) - Constructor for class org.deeplearning4j.nn.modelimport.keras.layers.core.KerasSpatialDropout
-
Pass-through constructor from KerasLayer
- KerasSpatialDropout(Map<String, Object>) - Constructor for class org.deeplearning4j.nn.modelimport.keras.layers.core.KerasSpatialDropout
-
Constructor from parsed Keras layer configuration dictionary.
- KerasSpatialDropout(Map<String, Object>, boolean) - Constructor for class org.deeplearning4j.nn.modelimport.keras.layers.core.KerasSpatialDropout
-
Constructor from parsed Keras layer configuration dictionary.
- KerasUpsampling1D - Class in org.deeplearning4j.nn.modelimport.keras.layers.convolutional
-
Keras Upsampling1D layer support
- KerasUpsampling1D(Map<String, Object>) - Constructor for class org.deeplearning4j.nn.modelimport.keras.layers.convolutional.KerasUpsampling1D
-
Constructor from parsed Keras layer configuration dictionary.
- KerasUpsampling1D(Map<String, Object>, boolean) - Constructor for class org.deeplearning4j.nn.modelimport.keras.layers.convolutional.KerasUpsampling1D
-
Constructor from parsed Keras layer configuration dictionary.
- KerasUpsampling2D - Class in org.deeplearning4j.nn.modelimport.keras.layers.convolutional
-
Keras Upsampling2D layer support
- KerasUpsampling2D(Map<String, Object>) - Constructor for class org.deeplearning4j.nn.modelimport.keras.layers.convolutional.KerasUpsampling2D
-
Constructor from parsed Keras layer configuration dictionary.
- KerasUpsampling2D(Map<String, Object>, boolean) - Constructor for class org.deeplearning4j.nn.modelimport.keras.layers.convolutional.KerasUpsampling2D
-
Constructor from parsed Keras layer configuration dictionary.
- KerasUpsampling3D - Class in org.deeplearning4j.nn.modelimport.keras.layers.convolutional
-
Keras Upsampling3D layer support
- KerasUpsampling3D(Map<String, Object>) - Constructor for class org.deeplearning4j.nn.modelimport.keras.layers.convolutional.KerasUpsampling3D
-
Constructor from parsed Keras layer configuration dictionary.
- KerasUpsampling3D(Map<String, Object>, boolean) - Constructor for class org.deeplearning4j.nn.modelimport.keras.layers.convolutional.KerasUpsampling3D
-
Constructor from parsed Keras layer configuration dictionary.
- KerasZeroPadding1D - Class in org.deeplearning4j.nn.modelimport.keras.layers.convolutional
-
Imports a Keras ZeroPadding 1D layer.
- KerasZeroPadding1D(Map<String, Object>) - Constructor for class org.deeplearning4j.nn.modelimport.keras.layers.convolutional.KerasZeroPadding1D
-
Constructor from parsed Keras layer configuration dictionary.
- KerasZeroPadding1D(Map<String, Object>, boolean) - Constructor for class org.deeplearning4j.nn.modelimport.keras.layers.convolutional.KerasZeroPadding1D
-
Constructor from parsed Keras layer configuration dictionary.
- KerasZeroPadding2D - Class in org.deeplearning4j.nn.modelimport.keras.layers.convolutional
-
Imports a Keras ZeroPadding 2D layer.
- KerasZeroPadding2D(Map<String, Object>) - Constructor for class org.deeplearning4j.nn.modelimport.keras.layers.convolutional.KerasZeroPadding2D
-
Constructor from parsed Keras layer configuration dictionary.
- KerasZeroPadding2D(Map<String, Object>, boolean) - Constructor for class org.deeplearning4j.nn.modelimport.keras.layers.convolutional.KerasZeroPadding2D
-
Constructor from parsed Keras layer configuration dictionary.
- KerasZeroPadding3D - Class in org.deeplearning4j.nn.modelimport.keras.layers.convolutional
-
Imports a Keras ZeroPadding 3D layer.
- KerasZeroPadding3D(Map<String, Object>) - Constructor for class org.deeplearning4j.nn.modelimport.keras.layers.convolutional.KerasZeroPadding3D
-
Constructor from parsed Keras layer configuration dictionary.
- KerasZeroPadding3D(Map<String, Object>, boolean) - Constructor for class org.deeplearning4j.nn.modelimport.keras.layers.convolutional.KerasZeroPadding3D
-
Constructor from parsed Keras layer configuration dictionary.
- kernelSize(int) - Method in class org.deeplearning4j.nn.conf.layers.Convolution1DLayer.Builder
-
Size of the convolution
- kernelSize(int...) - Method in class org.deeplearning4j.nn.conf.layers.Convolution3D.Builder
-
Set kernel size for 3D convolutions in (depth, height, width) order
- kernelSize - Variable in class org.deeplearning4j.nn.conf.layers.ConvolutionLayer.BaseConvBuilder
-
- kernelSize(int...) - Method in class org.deeplearning4j.nn.conf.layers.ConvolutionLayer.Builder
-
Size of the convolution
rows/columns
- kernelSize - Variable in class org.deeplearning4j.nn.conf.layers.ConvolutionLayer
-
- kernelSize(int...) - Method in class org.deeplearning4j.nn.conf.layers.Deconvolution2D.Builder
-
Size of the convolution
rows/columns
- kernelSize(int...) - Method in class org.deeplearning4j.nn.conf.layers.DepthwiseConvolution2D.Builder
-
Size of the convolution
rows/columns
- kernelSize(int...) - Method in class org.deeplearning4j.nn.conf.layers.SeparableConvolution2D.Builder
-
Size of the convolution
rows/columns
- kernelSize(int) - Method in class org.deeplearning4j.nn.conf.layers.Subsampling1DLayer.Builder
-
Kernel size
- kernelSize - Variable in class org.deeplearning4j.nn.conf.layers.Subsampling3DLayer.BaseSubsamplingBuilder
-
- kernelSize(int...) - Method in class org.deeplearning4j.nn.conf.layers.Subsampling3DLayer.Builder
-
Kernel size
- kernelSize - Variable in class org.deeplearning4j.nn.conf.layers.Subsampling3DLayer
-
- kernelSize - Variable in class org.deeplearning4j.nn.conf.layers.SubsamplingLayer.BaseSubsamplingBuilder
-
- kernelSize(int...) - Method in class org.deeplearning4j.nn.conf.layers.SubsamplingLayer.Builder
-
Kernel size
- kernelSize - Variable in class org.deeplearning4j.nn.conf.layers.SubsamplingLayer
-
- keys() - Static method in class org.ansj.library.AmbiguityLibrary
-
- keys() - Static method in class org.ansj.library.CrfLibrary
-
- keys() - Static method in class org.ansj.library.DicLibrary
-
- keys() - Static method in class org.ansj.library.StopLibrary
-
- keys() - Static method in class org.ansj.library.SynonymsLibrary
-
- keys() - Static method in class org.deeplearning4j.nn.params.BatchNormalizationParamInitializer
-
- KeySequenceConvertFunction - Class in org.deeplearning4j.spark.models.paragraphvectors.functions
-
- KeySequenceConvertFunction(Broadcast<VectorsConfiguration>) - Constructor for class org.deeplearning4j.spark.models.paragraphvectors.functions.KeySequenceConvertFunction
-
- keySet() - Method in class com.atilika.kuromoji.trie.PatriciaTrie
-
Returns a copy of the keys contained in this trie as a Set
- keysForBucket(String) - Method in class org.deeplearning4j.aws.s3.reader.S3Downloader
-
Return the keys for a bucket
- Keyword - Class in org.ansj.app.keyword
-
- Keyword(String, int, double) - Constructor for class org.ansj.app.keyword.Keyword
-
- Keyword(String, double) - Constructor for class org.ansj.app.keyword.Keyword
-
- KeyWordComputer<T extends Analysis> - Class in org.ansj.app.keyword
-
- KeyWordComputer() - Constructor for class org.ansj.app.keyword.KeyWordComputer
-
- KeyWordComputer(int) - Constructor for class org.ansj.app.keyword.KeyWordComputer
-
返回关键词个数
- KeyWordComputer(int, T) - Constructor for class org.ansj.app.keyword.KeyWordComputer
-
- KMeansClustering - Class in org.deeplearning4j.clustering.kmeans
-
- KMeansClustering(ClusteringStrategy) - Constructor for class org.deeplearning4j.clustering.kmeans.KMeansClustering
-
- knn(INDArray, double) - Method in class org.deeplearning4j.clustering.kdtree.KDTree
-
- knn(int, int) - Method in class org.deeplearning4j.nearestneighbor.client.NearestNeighborsClient
-
Runs knn on the given index
with the given k (note that this is for data
already within the existing dataset not new data)
- knnNew(int, INDArray) - Method in class org.deeplearning4j.nearestneighbor.client.NearestNeighborsClient
-
Run a k nearest neighbors search
on a NEW data point
- KoreanTokenizer - Class in org.deeplearning4j.text.tokenization.tokenizer
-
Created by kepricon on 16.
- KoreanTokenizer(String) - Constructor for class org.deeplearning4j.text.tokenization.tokenizer.KoreanTokenizer
-
- KoreanTokenizerFactory - Class in org.deeplearning4j.text.tokenization.tokenizerfactory
-
Created by kepricon on 16.
- KoreanTokenizerFactory() - Constructor for class org.deeplearning4j.text.tokenization.tokenizerfactory.KoreanTokenizerFactory
-
- kroneckerDelta(double, double) - Static method in class org.deeplearning4j.clustering.util.MathUtils
-
This returns the kronecker delta of two doubles.
- KUROMOJI_BIN_ROOT - Static variable in class com.atilika.kuromoji.util.KuromojiBinFilesFetcher
-
- KuromojiBinFilesFetcher - Class in com.atilika.kuromoji.util
-
Created by kepricon on 16.
- kuromojiExist() - Static method in class com.atilika.kuromoji.util.KuromojiBinFilesFetcher
-
- KV<K,V> - Class in org.ansj.domain
-
- l1 - Variable in class org.deeplearning4j.nn.conf.layers.BaseLayer.Builder
-
- l1(double) - Method in class org.deeplearning4j.nn.conf.layers.BaseLayer.Builder
-
L1 regularization coefficient (weights only).
- l1 - Variable in class org.deeplearning4j.nn.conf.layers.BaseLayer
-
- l1 - Variable in class org.deeplearning4j.nn.conf.layers.samediff.AbstractSameDiffLayer.Builder
-
- l1(double) - Method in class org.deeplearning4j.nn.conf.layers.samediff.AbstractSameDiffLayer.Builder
-
L1 regularization coefficient (weights only).
- l1 - Variable in class org.deeplearning4j.nn.conf.layers.samediff.AbstractSameDiffLayer
-
- l1 - Variable in class org.deeplearning4j.nn.conf.NeuralNetConfiguration.Builder
-
- l1(double) - Method in class org.deeplearning4j.nn.conf.NeuralNetConfiguration.Builder
-
L1 regularization coefficient for the weights.
Note: values set by this method will be applied to all applicable layers in the network, unless a different
value is explicitly set on a given layer.
- l1(double) - Method in class org.deeplearning4j.nn.transferlearning.FineTuneConfiguration.Builder
-
L1 regularization coefficient for the weights
- l1 - Variable in class org.deeplearning4j.nn.transferlearning.FineTuneConfiguration
-
- l1Bias - Variable in class org.deeplearning4j.nn.conf.layers.BaseLayer.Builder
-
- l1Bias(double) - Method in class org.deeplearning4j.nn.conf.layers.BaseLayer.Builder
-
L1 regularization coefficient for the bias.
- l1Bias - Variable in class org.deeplearning4j.nn.conf.layers.BaseLayer
-
- l1Bias - Variable in class org.deeplearning4j.nn.conf.layers.samediff.AbstractSameDiffLayer.Builder
-
- l1Bias(double) - Method in class org.deeplearning4j.nn.conf.layers.samediff.AbstractSameDiffLayer.Builder
-
L1 regularization coefficient for the bias.
- l1Bias - Variable in class org.deeplearning4j.nn.conf.layers.samediff.AbstractSameDiffLayer
-
- l1Bias - Variable in class org.deeplearning4j.nn.conf.NeuralNetConfiguration.Builder
-
- l1Bias(double) - Method in class org.deeplearning4j.nn.conf.NeuralNetConfiguration.Builder
-
L1 regularization coefficient for the bias.
Note: values set by this method will be applied to all applicable layers in the network, unless a different
value is explicitly set on a given layer.
- l1Bias(double) - Method in class org.deeplearning4j.nn.transferlearning.FineTuneConfiguration.Builder
-
L1 regularization coefficient for the bias parameters
- l1Bias - Variable in class org.deeplearning4j.nn.transferlearning.FineTuneConfiguration
-
- l1ByParam - Variable in class org.deeplearning4j.nn.conf.NeuralNetConfiguration
-
- l2 - Variable in class org.deeplearning4j.nn.conf.layers.BaseLayer.Builder
-
- l2(double) - Method in class org.deeplearning4j.nn.conf.layers.BaseLayer.Builder
-
L2 regularization coefficient (weights only).
- l2 - Variable in class org.deeplearning4j.nn.conf.layers.BaseLayer
-
- l2 - Variable in class org.deeplearning4j.nn.conf.layers.samediff.AbstractSameDiffLayer.Builder
-
- l2(double) - Method in class org.deeplearning4j.nn.conf.layers.samediff.AbstractSameDiffLayer.Builder
-
L2 regularization coefficient (weights only).
- l2 - Variable in class org.deeplearning4j.nn.conf.layers.samediff.AbstractSameDiffLayer
-
- l2 - Variable in class org.deeplearning4j.nn.conf.NeuralNetConfiguration.Builder
-
- l2(double) - Method in class org.deeplearning4j.nn.conf.NeuralNetConfiguration.Builder
-
L2 regularization coefficient for the weights.
Note: values set by this method will be applied to all applicable layers in the network, unless a different
value is explicitly set on a given layer.
- l2(double) - Method in class org.deeplearning4j.nn.transferlearning.FineTuneConfiguration.Builder
-
L2 regularization coefficient for the weights
- l2 - Variable in class org.deeplearning4j.nn.transferlearning.FineTuneConfiguration
-
- l2Bias - Variable in class org.deeplearning4j.nn.conf.layers.BaseLayer.Builder
-
- l2Bias(double) - Method in class org.deeplearning4j.nn.conf.layers.BaseLayer.Builder
-
L2 regularization coefficient for the bias.
- l2Bias - Variable in class org.deeplearning4j.nn.conf.layers.BaseLayer
-
- l2Bias - Variable in class org.deeplearning4j.nn.conf.layers.samediff.AbstractSameDiffLayer.Builder
-
- l2Bias(double) - Method in class org.deeplearning4j.nn.conf.layers.samediff.AbstractSameDiffLayer.Builder
-
L2 regularization coefficient for the bias.
- l2Bias - Variable in class org.deeplearning4j.nn.conf.layers.samediff.AbstractSameDiffLayer
-
- l2Bias - Variable in class org.deeplearning4j.nn.conf.NeuralNetConfiguration.Builder
-
- l2Bias(double) - Method in class org.deeplearning4j.nn.conf.NeuralNetConfiguration.Builder
-
L2 regularization coefficient for the bias.
Note: values set by this method will be applied to all applicable layers in the network, unless a different
value is explicitly set on a given layer.
- l2Bias(double) - Method in class org.deeplearning4j.nn.transferlearning.FineTuneConfiguration.Builder
-
L2 regularization coefficient for the bias parameters
- l2Bias - Variable in class org.deeplearning4j.nn.transferlearning.FineTuneConfiguration
-
- l2ByParam - Variable in class org.deeplearning4j.nn.conf.NeuralNetConfiguration
-
- L2NormalizeVertex - Class in org.deeplearning4j.nn.conf.graph
-
L2NormalizeVertex performs L2 normalization on a single input.
- L2NormalizeVertex() - Constructor for class org.deeplearning4j.nn.conf.graph.L2NormalizeVertex
-
- L2NormalizeVertex(int[], double) - Constructor for class org.deeplearning4j.nn.conf.graph.L2NormalizeVertex
-
- L2NormalizeVertex - Class in org.deeplearning4j.nn.graph.vertex.impl
-
L2NormalizeVertex performs L2 normalization on a single input.
- L2NormalizeVertex(ComputationGraph, String, int, int[], double) - Constructor for class org.deeplearning4j.nn.graph.vertex.impl.L2NormalizeVertex
-
- L2NormalizeVertex(ComputationGraph, String, int, VertexIndices[], VertexIndices[], int[], double) - Constructor for class org.deeplearning4j.nn.graph.vertex.impl.L2NormalizeVertex
-
- L2Vertex - Class in org.deeplearning4j.nn.conf.graph
-
L2Vertex calculates the L2 least squares error of two inputs.
- L2Vertex() - Constructor for class org.deeplearning4j.nn.conf.graph.L2Vertex
-
- L2Vertex(double) - Constructor for class org.deeplearning4j.nn.conf.graph.L2Vertex
-
- L2Vertex - Class in org.deeplearning4j.nn.graph.vertex.impl
-
L2Vertex calculates the L2 least squares error of two inputs.
- L2Vertex(ComputationGraph, String, int, double) - Constructor for class org.deeplearning4j.nn.graph.vertex.impl.L2Vertex
-
- L2Vertex(ComputationGraph, String, int, VertexIndices[], VertexIndices[], double) - Constructor for class org.deeplearning4j.nn.graph.vertex.impl.L2Vertex
-
- label - Variable in class org.deeplearning4j.models.sequencevectors.sequence.Sequence
-
- label() - Method in class org.deeplearning4j.nn.layers.feedforward.autoencoder.recursive.Tree
-
- LabelAwareConverter - Class in org.deeplearning4j.iterator.provider
-
Simple class for conversion between LabelAwareIterator -> LabeledSentenceProvider for neural nets.
- LabelAwareConverter(LabelAwareIterator, List<String>) - Constructor for class org.deeplearning4j.iterator.provider.LabelAwareConverter
-
- LabelAwareDocumentIterator - Interface in org.deeplearning4j.text.documentiterator
-
Created by agibsonccc on 10/18/14.
- LabelAwareFileSentenceIterator - Class in org.deeplearning4j.text.sentenceiterator.labelaware
-
Label aware sentence iterator
- LabelAwareFileSentenceIterator(SentencePreProcessor, File) - Constructor for class org.deeplearning4j.text.sentenceiterator.labelaware.LabelAwareFileSentenceIterator
-
Takes a single file or directory
- LabelAwareFileSentenceIterator(File) - Constructor for class org.deeplearning4j.text.sentenceiterator.labelaware.LabelAwareFileSentenceIterator
-
- labelAwareIterator - Variable in class org.deeplearning4j.models.paragraphvectors.ParagraphVectors.Builder
-
- labelAwareIterator - Variable in class org.deeplearning4j.models.paragraphvectors.ParagraphVectors
-
- labelAwareIterator - Variable in class org.deeplearning4j.models.word2vec.Word2Vec.Builder
-
- LabelAwareIterator - Interface in org.deeplearning4j.text.documentiterator
-
This simple iterator interface assumes, that all documents are packed into strings OR into references to VocabWords.
- LabelAwareSentenceIterator - Interface in org.deeplearning4j.text.sentenceiterator.labelaware
-
SentenceIterator that is aware of its label.
- LabelAwareUimaSentenceIterator - Class in org.deeplearning4j.text.sentenceiterator.labelaware
-
Uima sentence iterator that is aware of the current file
- LabelAwareUimaSentenceIterator(SentencePreProcessor, String, UimaResource) - Constructor for class org.deeplearning4j.text.sentenceiterator.labelaware.LabelAwareUimaSentenceIterator
-
- LabelAwareUimaSentenceIterator(String, AnalysisEngine) - Constructor for class org.deeplearning4j.text.sentenceiterator.labelaware.LabelAwareUimaSentenceIterator
-
- LabeledSentenceProvider - Interface in org.deeplearning4j.iterator
-
LabeledSentenceProvider: a simple iterator interface over sentences/documents that have a label.
This is intended for use with
CnnSentenceDataSetIterator
- labelIndex - Variable in class org.deeplearning4j.datasets.datavec.RecordReaderDataSetIterator.Builder
-
- labelIndex - Variable in class org.deeplearning4j.datasets.datavec.RecordReaderDataSetIterator
-
- labelIndexTo - Variable in class org.deeplearning4j.datasets.datavec.RecordReaderDataSetIterator.Builder
-
- labelIndexTo - Variable in class org.deeplearning4j.datasets.datavec.RecordReaderDataSetIterator
-
- LabelledDocument - Class in org.deeplearning4j.text.documentiterator
-
This is primitive holder of document, and it's label.
- LabelledDocument() - Constructor for class org.deeplearning4j.text.documentiterator.LabelledDocument
-
- labelProbabilities(INDArray) - Method in interface org.deeplearning4j.nn.api.Classifier
-
Returns the probabilities for each label
for each example row wise
- labelProbabilities(INDArray) - Method in class org.deeplearning4j.nn.layers.BaseOutputLayer
-
Returns the probabilities for each label
for each example row wise
- labelProbabilities(INDArray) - Method in class org.deeplearning4j.nn.layers.convolution.CnnLossLayer
-
- labelProbabilities(INDArray) - Method in class org.deeplearning4j.nn.layers.LossLayer
-
Returns the probabilities for each label
for each example row wise
- labelProbabilities(INDArray) - Method in class org.deeplearning4j.nn.layers.objdetect.Yolo2OutputLayer
-
- labelProbabilities(INDArray) - Method in class org.deeplearning4j.nn.layers.ocnn.OCNNOutputLayer
-
- labelProbabilities(INDArray) - Method in class org.deeplearning4j.nn.layers.recurrent.RnnLossLayer
-
- labelProbabilities(INDArray) - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
-
Returns the probabilities for each label
for each example row wise
- labels - Variable in class org.deeplearning4j.bagofwords.vectorizer.Builder
-
Deprecated.
- labels(List<String>) - Method in class org.deeplearning4j.bagofwords.vectorizer.Builder
-
Deprecated.
- labels(List<String>) - Method in class org.deeplearning4j.models.paragraphvectors.ParagraphVectors.Builder
-
Deprecated.
- labels - Variable in class org.deeplearning4j.models.sequencevectors.sequence.Sequence
-
- labels - Variable in class org.deeplearning4j.nn.layers.BaseOutputLayer
-
- labels - Variable in class org.deeplearning4j.nn.layers.convolution.CnnLossLayer
-
- labels - Variable in class org.deeplearning4j.nn.layers.LossLayer
-
- labels - Variable in class org.deeplearning4j.nn.layers.objdetect.Yolo2OutputLayer
-
- labels - Variable in class org.deeplearning4j.nn.layers.recurrent.RnnLossLayer
-
- labels - Variable in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
-
- labels - Variable in class org.deeplearning4j.text.documentiterator.SimpleLabelAwareIterator
-
- labels - Variable in class org.deeplearning4j.zoo.util.BaseLabels
-
- Labels - Interface in org.deeplearning4j.zoo.util
-
Interface to helper classes that return label descriptions.
- labelsList - Variable in class org.deeplearning4j.eval.Evaluation
-
- labelsList - Variable in class org.deeplearning4j.models.paragraphvectors.ParagraphVectors
-
- labelsMatrix - Variable in class org.deeplearning4j.models.paragraphvectors.ParagraphVectors
-
- labelsProvider - Variable in class org.deeplearning4j.models.sequencevectors.transformers.impl.GraphTransformer.Builder
-
- labelsProvider - Variable in class org.deeplearning4j.models.sequencevectors.transformers.impl.GraphTransformer
-
- LabelsProvider<T extends SequenceElement> - Interface in org.deeplearning4j.text.labels
-
- labelsSource - Variable in class org.deeplearning4j.bagofwords.vectorizer.BagOfWordsVectorizer.Builder
-
- labelsSource - Variable in class org.deeplearning4j.bagofwords.vectorizer.BaseTextVectorizer
-
- labelsSource - Variable in class org.deeplearning4j.bagofwords.vectorizer.TfidfVectorizer.Builder
-
- labelsSource - Variable in class org.deeplearning4j.models.paragraphvectors.ParagraphVectors.Builder
-
- labelsSource(LabelsSource) - Method in class org.deeplearning4j.models.paragraphvectors.ParagraphVectors.Builder
-
This method attaches pre-defined labels source to ParagraphVectors
- labelsSource - Variable in class org.deeplearning4j.models.paragraphvectors.ParagraphVectors
-
- labelsSource - Variable in class org.deeplearning4j.text.documentiterator.FileLabelAwareIterator
-
- labelsSource - Variable in class org.deeplearning4j.text.documentiterator.FilenamesLabelAwareIterator
-
- LabelsSource - Class in org.deeplearning4j.text.documentiterator
-
This class is used to manage labels/documents syncronization over iterators
- LabelsSource() - Constructor for class org.deeplearning4j.text.documentiterator.LabelsSource
-
- LabelsSource(String) - Constructor for class org.deeplearning4j.text.documentiterator.LabelsSource
-
Build LabelsSource using string template.
- LabelsSource(List<String>) - Constructor for class org.deeplearning4j.text.documentiterator.LabelsSource
-
Build LabelsSource using externally defined list of string labels.
- lambbaNoObj(double) - Method in class org.deeplearning4j.nn.conf.layers.objdetect.Yolo2OutputLayer.Builder
-
Loss function coefficient for the "no object confidence" components of the loss function.
- lambda - Variable in class org.deeplearning4j.nn.conf.layers.CenterLossOutputLayer.Builder
-
- lambda(double) - Method in class org.deeplearning4j.nn.conf.layers.CenterLossOutputLayer.Builder
-
- lambda - Variable in class org.deeplearning4j.nn.conf.layers.CenterLossOutputLayer
-
- lambdaCoord(double) - Method in class org.deeplearning4j.nn.conf.layers.objdetect.Yolo2OutputLayer.Builder
-
Loss function coefficient for position and size/scale components of the loss function.
- last - Variable in class org.deeplearning4j.datasets.datavec.RecordReaderDataSetIterator
-
- lastAct - Variable in class org.deeplearning4j.nn.layers.recurrent.FwdPassReturn
-
- lastBatch - Variable in class org.deeplearning4j.datasets.iterator.MultipleEpochsIterator
-
Deprecated.
- lastBP - Variable in class org.deeplearning4j.optimize.listeners.SleepyTrainingListener
-
- lastChecked(int) - Method in class org.deeplearning4j.spark.models.embeddings.word2vec.Word2VecParam.Builder
-
Deprecated.
- lastCheckpoint() - Method in class org.deeplearning4j.optimize.listeners.checkpoint.CheckpointListener
-
Return the most recent checkpoint, if one exists - otherwise returns null
- lastChild() - Method in class org.deeplearning4j.nn.layers.feedforward.autoencoder.recursive.Tree
-
- lastEE - Variable in class org.deeplearning4j.optimize.listeners.SleepyTrainingListener
-
- lastES - Variable in class org.deeplearning4j.optimize.listeners.SleepyTrainingListener
-
- lastEtlTime - Variable in class org.deeplearning4j.nn.graph.ComputationGraph
-
- lastEtlTime - Variable in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
-
- lastEtlTime - Variable in class org.deeplearning4j.parallelism.trainer.DefaultTrainer
-
- lastExportedRDDId - Variable in class org.deeplearning4j.spark.impl.paramavg.BaseTrainingMaster
-
- lastFF - Variable in class org.deeplearning4j.optimize.listeners.SleepyTrainingListener
-
- lastIteration - Variable in class org.deeplearning4j.optimize.listeners.SleepyTrainingListener
-
- lastMemCell - Variable in class org.deeplearning4j.nn.layers.recurrent.FwdPassReturn
-
- lastRDDExportPath - Variable in class org.deeplearning4j.spark.impl.paramavg.BaseTrainingMaster
-
- lastStep - Variable in class org.deeplearning4j.optimize.solvers.accumulation.EncodingHandler
-
- LastTimeStep - Class in org.deeplearning4j.nn.conf.layers.recurrent
-
LastTimeStep is a "wrapper" layer: it wraps any RNN layer, and extracts out the last time step during forward pass,
and returns it as a row vector (per example).
- LastTimeStep(Layer) - Constructor for class org.deeplearning4j.nn.conf.layers.recurrent.LastTimeStep
-
- LastTimeStepLayer - Class in org.deeplearning4j.nn.layers.recurrent
-
LastTimeStep is a "wrapper" layer: it wraps any RNN layer, and extracts out the last time step during forward pass,
and returns it as a row vector (per example).
- LastTimeStepLayer(Layer) - Constructor for class org.deeplearning4j.nn.layers.recurrent.LastTimeStepLayer
-
- LastTimeStepVertex - Class in org.deeplearning4j.nn.conf.graph.rnn
-
LastTimeStepVertex is used in the context of recurrent neural network activations, to go from 3d (time series)
activations to 2d activations, by extracting out the last time step of activations for each example.
This can be used for example in sequence to sequence architectures, and potentially for sequence classification.
- LastTimeStepVertex(String) - Constructor for class org.deeplearning4j.nn.conf.graph.rnn.LastTimeStepVertex
-
- LastTimeStepVertex - Class in org.deeplearning4j.nn.graph.vertex.impl.rnn
-
LastTimeStepVertex is used in the context of recurrent neural network activations, to go from 3d (time series)
activations to 2d activations, by extracting out the last time step of activations for each example.
This can be used for example in sequence to sequence architectures, and potentially for sequence classification.
- LastTimeStepVertex(ComputationGraph, String, int, String) - Constructor for class org.deeplearning4j.nn.graph.vertex.impl.rnn.LastTimeStepVertex
-
- LastTimeStepVertex(ComputationGraph, String, int, VertexIndices[], VertexIndices[], String) - Constructor for class org.deeplearning4j.nn.graph.vertex.impl.rnn.LastTimeStepVertex
-
- Layer - Interface in org.deeplearning4j.nn.api
-
Interface for a layer of a neural network.
- layer(int, Layer, String...) - Method in class org.deeplearning4j.nn.conf.ComputationGraphConfiguration.GraphBuilder
-
Add a layer, with no
InputPreProcessor, with the specified name and specified inputs.
- layer(String, Layer, String...) - Method in class org.deeplearning4j.nn.conf.ComputationGraphConfiguration.GraphBuilder
-
Add a layer, with no
InputPreProcessor, with the specified name and specified inputs.
- layer(String, Layer, InputPreProcessor, String...) - Method in class org.deeplearning4j.nn.conf.ComputationGraphConfiguration.GraphBuilder
-
- Layer - Class in org.deeplearning4j.nn.conf.layers
-
A neural network layer.
- Layer(Layer.Builder) - Constructor for class org.deeplearning4j.nn.conf.layers.Layer
-
- layer(Layer) - Method in class org.deeplearning4j.nn.conf.layers.misc.FrozenLayer.Builder
-
- layer - Variable in class org.deeplearning4j.nn.conf.layers.misc.FrozenLayer
-
- layer - Variable in class org.deeplearning4j.nn.conf.NeuralNetConfiguration.Builder
-
- layer(Layer) - Method in class org.deeplearning4j.nn.conf.NeuralNetConfiguration.Builder
-
Layer class.
- layer - Variable in class org.deeplearning4j.nn.conf.NeuralNetConfiguration
-
- layer(int, Layer) - Method in class org.deeplearning4j.nn.conf.NeuralNetConfiguration.ListBuilder
-
- layer(Layer) - Method in class org.deeplearning4j.nn.conf.NeuralNetConfiguration.ListBuilder
-
- layer - Variable in class org.deeplearning4j.nn.modelimport.keras.KerasLayer
-
- Layer.Builder<T extends Layer.Builder<T>> - Class in org.deeplearning4j.nn.conf.layers
-
- Layer.TrainingMode - Enum in org.deeplearning4j.nn.api
-
- Layer.Type - Enum in org.deeplearning4j.nn.api
-
- layerConf() - Method in class org.deeplearning4j.nn.layers.AbstractLayer
-
- layerConf() - Method in class org.deeplearning4j.nn.layers.BaseLayer
-
- layerConf() - Method in class org.deeplearning4j.nn.layers.variational.VariationalAutoencoder
-
- LayerConstraint - Interface in org.deeplearning4j.nn.api.layers
-
- layerId() - Method in class org.deeplearning4j.nn.layers.AbstractLayer
-
- layerId() - Method in class org.deeplearning4j.nn.layers.FrozenLayer
-
- layerId() - Method in class org.deeplearning4j.nn.layers.FrozenLayerWithBackprop
-
- layerId() - Method in class org.deeplearning4j.nn.layers.variational.VariationalAutoencoder
-
- layerIndex - Variable in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
-
- layerInputSize(int) - Method in class org.deeplearning4j.nn.graph.ComputationGraph
-
Return the input size (number of inputs) for the specified layer.
Note that the meaning of the "input size" can depend on the type of layer.
- layerInputSize(String) - Method in class org.deeplearning4j.nn.graph.ComputationGraph
-
Return the input size (number of inputs) for the specified layer.
Note that the meaning of the "input size" can depend on the type of layer.
- layerInputSize(int) - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
-
Return the input size (number of inputs) for the specified layer.
Note that the meaning of the "input size" can depend on the type of layer.
- layerMap - Variable in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
-
- LayerMemoryReport - Class in org.deeplearning4j.nn.conf.memory
-
A
MemoryReport Designed to report estimated memory use for a single layer or graph vertex.
- LayerMemoryReport(LayerMemoryReport.Builder) - Constructor for class org.deeplearning4j.nn.conf.memory.LayerMemoryReport
-
- LayerMemoryReport.Builder - Class in org.deeplearning4j.nn.conf.memory
-
- layerName - Variable in class org.deeplearning4j.nn.conf.layers.Layer.Builder
-
- layerName - Variable in class org.deeplearning4j.nn.conf.layers.Layer
-
- layerName - Variable in class org.deeplearning4j.nn.modelimport.keras.KerasLayer
-
- layerName() - Method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder.LayerNamesDecoder
-
- layerName(String) - Method in class org.deeplearning4j.ui.stats.sbe.UpdateEncoder.LayerNamesEncoder
-
- layerNameCharacterEncoding() - Static method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder.LayerNamesDecoder
-
- layerNameCharacterEncoding() - Static method in class org.deeplearning4j.ui.stats.sbe.UpdateEncoder.LayerNamesEncoder
-
- layerNameHeaderLength() - Static method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder.LayerNamesDecoder
-
- layerNameHeaderLength() - Static method in class org.deeplearning4j.ui.stats.sbe.UpdateEncoder.LayerNamesEncoder
-
- layerNameId() - Static method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder.LayerNamesDecoder
-
- layerNameId() - Static method in class org.deeplearning4j.ui.stats.sbe.UpdateEncoder.LayerNamesEncoder
-
- layerNameLength() - Method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder.LayerNamesDecoder
-
- layerNameMetaAttribute(MetaAttribute) - Static method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder.LayerNamesDecoder
-
- layerNameMetaAttribute(MetaAttribute) - Static method in class org.deeplearning4j.ui.stats.sbe.UpdateEncoder.LayerNamesEncoder
-
- layerNames() - Method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder
-
- layerNamesCount(int) - Method in class org.deeplearning4j.ui.stats.sbe.UpdateEncoder
-
- LayerNamesDecoder() - Constructor for class org.deeplearning4j.ui.stats.sbe.UpdateDecoder.LayerNamesDecoder
-
- layerNamesDecoderId() - Static method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder
-
- LayerNamesEncoder() - Constructor for class org.deeplearning4j.ui.stats.sbe.UpdateEncoder.LayerNamesEncoder
-
- layerNamesId() - Static method in class org.deeplearning4j.ui.stats.sbe.UpdateEncoder
-
- layers - Variable in class org.deeplearning4j.nn.graph.ComputationGraph
-
A list of layers.
- layers - Variable in class org.deeplearning4j.nn.modelimport.keras.KerasModel
-
- layers - Variable in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
-
- layersByName - Variable in class org.deeplearning4j.nn.updater.BaseMultiLayerUpdater
-
- layerSize() - Method in class org.deeplearning4j.models.embeddings.inmemory.InMemoryLookupTable
-
- layerSize() - Method in interface org.deeplearning4j.models.embeddings.WeightLookupTable
-
The layer size for the lookup table
- layerSize - Variable in class org.deeplearning4j.models.embeddings.wordvectors.WordVectorsImpl
-
- layerSize(int) - Method in class org.deeplearning4j.models.glove.Glove.Builder
-
- layerSize(int) - Method in class org.deeplearning4j.models.node2vec.Node2Vec.Builder
-
Deprecated.
- layerSize(int) - Method in class org.deeplearning4j.models.paragraphvectors.ParagraphVectors.Builder
-
This method defines number of dimensions for output vectors
- layerSize - Variable in class org.deeplearning4j.models.sequencevectors.SequenceVectors.Builder
-
- layerSize(int) - Method in class org.deeplearning4j.models.sequencevectors.SequenceVectors.Builder
-
This method defines number of dimensions for outcome vectors.
- layerSize(int) - Method in class org.deeplearning4j.models.word2vec.Word2Vec.Builder
-
This method defines number of dimensions for output vectors
- layerSize(int) - Method in class org.deeplearning4j.nn.graph.ComputationGraph
-
Return the layer size (number of units) for the specified layer.
- layerSize(String) - Method in class org.deeplearning4j.nn.graph.ComputationGraph
-
Return the layer size (number of units) for the specified layer.
Note that the meaning of the "layer size" can depend on the type of layer.
- layerSize(int) - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
-
Return the layer size (number of units) for the specified layer.
Note that the meaning of the "layer size" can depend on the type of layer.
- layerSize - Variable in class org.deeplearning4j.spark.models.embeddings.word2vec.Word2Vec.Builder
-
- layerSize(int) - Method in class org.deeplearning4j.spark.models.embeddings.word2vec.Word2Vec.Builder
-
Specifies output vector's dimensions
- layerSize(int) - Method in class org.deeplearning4j.spark.models.sequencevectors.SparkSequenceVectors.Builder
-
- layerSize(int) - Method in class org.deeplearning4j.spark.models.word2vec.SparkWord2Vec.Builder
-
- layersOrdered - Variable in class org.deeplearning4j.nn.modelimport.keras.KerasModel
-
- LayerUpdater - Class in org.deeplearning4j.nn.updater
-
Updater for a single layer, excluding MultiLayerNetwork (which also implements the Layer interface)
- LayerUpdater(Layer) - Constructor for class org.deeplearning4j.nn.updater.LayerUpdater
-
- LayerUpdater(Layer, INDArray) - Constructor for class org.deeplearning4j.nn.updater.LayerUpdater
-
- LayerValidation - Class in org.deeplearning4j.nn.conf.layers
-
Created by Alex on 22/02/2017.
- LayerValidation() - Constructor for class org.deeplearning4j.nn.conf.layers.LayerValidation
-
- LayerVertex - Class in org.deeplearning4j.nn.conf.graph
-
LayerVertex is a GraphVertex with a neural network Layer (and, optionally an
InputPreProcessor) in it
- LayerVertex(NeuralNetConfiguration, InputPreProcessor) - Constructor for class org.deeplearning4j.nn.conf.graph.LayerVertex
-
- LayerVertex - Class in org.deeplearning4j.nn.graph.vertex.impl
-
LayerVertex is a GraphVertex with a neural network Layer (and, optionally an
InputPreProcessor) in it
- LayerVertex(ComputationGraph, String, int, Layer, InputPreProcessor, boolean) - Constructor for class org.deeplearning4j.nn.graph.vertex.impl.LayerVertex
-
Create a network input vertex:
- LayerVertex(ComputationGraph, String, int, VertexIndices[], VertexIndices[], Layer, InputPreProcessor, boolean) - Constructor for class org.deeplearning4j.nn.graph.vertex.impl.LayerVertex
-
- layerWiseConfigurations - Variable in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
-
- LayerWorkspaceMgr - Class in org.deeplearning4j.nn.workspace
-
WorkspaceMgr for DL4J layers.
- LayerWorkspaceMgr(Set<ArrayType>, Map<ArrayType, WorkspaceConfiguration>, Map<ArrayType, String>) - Constructor for class org.deeplearning4j.nn.workspace.LayerWorkspaceMgr
-
- LayerWorkspaceMgr.Builder - Class in org.deeplearning4j.nn.workspace
-
- LBFGS - Class in org.deeplearning4j.optimize.solvers
-
LBFGS
- LBFGS(NeuralNetConfiguration, StepFunction, Collection<TrainingListener>, Model) - Constructor for class org.deeplearning4j.optimize.solvers.LBFGS
-
- LBFGS(NeuralNetConfiguration, StepFunction, Collection<TrainingListener>, Collection<TerminationCondition>, Model) - Constructor for class org.deeplearning4j.optimize.solvers.LBFGS
-
- learn(Graph, SplitWord, Forest...) - Method in class org.ansj.dic.LearnTool
-
公司名称学习.
- learningRate(double) - Method in class org.deeplearning4j.graph.models.deepwalk.DeepWalk.Builder
-
Set the learning rate
- learningRate - Variable in class org.deeplearning4j.graph.models.embeddings.InMemoryGraphLookupTable
-
- learningRate - Variable in class org.deeplearning4j.models.embeddings.learning.impl.elements.GloVe.Builder
-
- learningRate(double) - Method in class org.deeplearning4j.models.embeddings.learning.impl.elements.GloVe.Builder
-
Initial learning rate; default 0.05
- learningRate - Variable in class org.deeplearning4j.models.embeddings.learning.impl.elements.GloVe
-
- learningRate - Variable in class org.deeplearning4j.models.embeddings.wordvectors.WordVectorsImpl
-
- learningRate(double) - Method in class org.deeplearning4j.models.glove.Glove.Builder
-
- learningRate(double) - Method in class org.deeplearning4j.models.node2vec.Node2Vec.Builder
-
Deprecated.
- learningRate(double) - Method in class org.deeplearning4j.models.paragraphvectors.ParagraphVectors.Builder
-
This method defines initial learning rate for model training
- learningRate - Variable in class org.deeplearning4j.models.sequencevectors.SequenceVectors.Builder
-
- learningRate(double) - Method in class org.deeplearning4j.models.sequencevectors.SequenceVectors.Builder
-
This method defines initial learning rate.
- learningRate(double) - Method in class org.deeplearning4j.models.word2vec.Word2Vec.Builder
-
This method defines initial learning rate for model training
- learningRate(double) - Method in class org.deeplearning4j.plot.BarnesHutTsne.Builder
-
- learningRate - Variable in class org.deeplearning4j.plot.BarnesHutTsne
-
- learningRate - Variable in class org.deeplearning4j.plot.Tsne.Builder
-
- learningRate(double) - Method in class org.deeplearning4j.plot.Tsne.Builder
-
- learningRate - Variable in class org.deeplearning4j.plot.Tsne
-
- learningRate - Variable in class org.deeplearning4j.spark.models.embeddings.word2vec.Word2Vec.Builder
-
- learningRate(double) - Method in class org.deeplearning4j.spark.models.embeddings.word2vec.Word2Vec.Builder
-
This method specifies initial learning rate for model
- learningRate() - Method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder.PerParameterStatsDecoder
-
- learningRate(float) - Method in class org.deeplearning4j.ui.stats.sbe.UpdateEncoder.PerParameterStatsEncoder
-
- learningRateDecayWords - Variable in class org.deeplearning4j.models.embeddings.wordvectors.WordVectorsImpl
-
- learningRateDecayWords - Variable in class org.deeplearning4j.models.sequencevectors.SequenceVectors.Builder
-
- learningRateId() - Static method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder.PerParameterStatsDecoder
-
- learningRateMaxValue() - Static method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder.PerParameterStatsDecoder
-
- learningRateMaxValue() - Static method in class org.deeplearning4j.ui.stats.sbe.UpdateEncoder.PerParameterStatsEncoder
-
- learningRateMetaAttribute(MetaAttribute) - Static method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder.PerParameterStatsDecoder
-
- learningRateMinValue() - Static method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder.PerParameterStatsDecoder
-
- learningRateMinValue() - Static method in class org.deeplearning4j.ui.stats.sbe.UpdateEncoder.PerParameterStatsEncoder
-
- learningRateNullValue() - Static method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder.PerParameterStatsDecoder
-
- learningRateNullValue() - Static method in class org.deeplearning4j.ui.stats.sbe.UpdateEncoder.PerParameterStatsEncoder
-
- learningRatesPresent() - Method in class org.deeplearning4j.ui.stats.sbe.UpdateFieldsPresentDecoder
-
- learningRatesPresent(boolean) - Method in class org.deeplearning4j.ui.stats.sbe.UpdateFieldsPresentEncoder
-
- learnSequence(Sequence<T>, AtomicLong, double) - Method in interface org.deeplearning4j.models.embeddings.learning.ElementsLearningAlgorithm
-
This method does training over the sequence of elements passed into it
- learnSequence(Sequence<T>, AtomicLong, double) - Method in class org.deeplearning4j.models.embeddings.learning.impl.elements.CBOW
-
- learnSequence(Sequence<T>, AtomicLong, double) - Method in class org.deeplearning4j.models.embeddings.learning.impl.elements.GloVe
-
Learns sequence using GloVe algorithm
- learnSequence(Sequence<T>, AtomicLong, double) - Method in class org.deeplearning4j.models.embeddings.learning.impl.elements.SkipGram
-
Learns sequence using SkipGram algorithm
- learnSequence(Sequence<T>, AtomicLong, double) - Method in class org.deeplearning4j.models.embeddings.learning.impl.sequence.DBOW
-
- learnSequence(Sequence<T>, AtomicLong, double) - Method in class org.deeplearning4j.models.embeddings.learning.impl.sequence.DM
-
- learnSequence(Sequence<T>, AtomicLong, double) - Method in interface org.deeplearning4j.models.embeddings.learning.SequenceLearningAlgorithm
-
This method does training over the sequence of elements passed into it
- learnSequence(Sequence<ShallowSequenceElement>, AtomicLong, double) - Method in class org.deeplearning4j.spark.models.sequencevectors.learning.elements.BaseSparkLearningAlgorithm
-
- LearnTool - Class in org.ansj.dic
-
新词发现,这是个线程安全的.所以可以多个对象公用一个
- LearnTool() - Constructor for class org.ansj.dic.LearnTool
-
- LEFT_ID - Static variable in class com.atilika.kuromoji.dict.DictionaryField
-
- leftId - Variable in class com.atilika.kuromoji.dict.DictionaryEntryBase
-
- leftId(short) - Method in class com.atilika.kuromoji.dict.GenericDictionaryEntry.Builder
-
- legacyAveraging - Variable in class org.deeplearning4j.parallelism.ParallelWrapper.Builder
-
- legacyAveraging - Variable in class org.deeplearning4j.parallelism.ParallelWrapper
-
- LegacyDistributionDeserializer - Class in org.deeplearning4j.nn.conf.distribution.serde
-
Jackson Json deserializer to handle legacy format for distributions.
Now, we use 'type' field which contains class information.
Previously, we used wrapper objects for type information instead (see TestDistributionDeserializer for examples)
- LegacyDistributionDeserializer() - Constructor for class org.deeplearning4j.nn.conf.distribution.serde.LegacyDistributionDeserializer
-
- LegacyDistributionHelper - Class in org.deeplearning4j.nn.conf.distribution.serde
-
A dummy helper "distribution" for deserializing distributions in legacy/different JSON format.
- LegacyGraphVertexDeserializer - Class in org.deeplearning4j.nn.conf.serde.legacyformat
-
Deserializer for GraphVertex JSON in legacy format - see BaseLegacyDeserializer
- LegacyGraphVertexDeserializer() - Constructor for class org.deeplearning4j.nn.conf.serde.legacyformat.LegacyGraphVertexDeserializer
-
- LegacyGraphVertexDeserializerHelper - Class in org.deeplearning4j.nn.conf.serde.legacyformat
-
- LegacyIntArrayDeserializer - Class in org.deeplearning4j.nn.conf.serde.legacyformat
-
Deserialize either an int[] to an int[], or a single int x to int[]{x,x}
Used when supporting a configuration format change from single int value to int[], as for Upsampling2D
between 1.0.0-alpha and 1.0.0-beta
- LegacyIntArrayDeserializer() - Constructor for class org.deeplearning4j.nn.conf.serde.legacyformat.LegacyIntArrayDeserializer
-
- LegacyLayerDeserializer - Class in org.deeplearning4j.nn.conf.serde.legacyformat
-
Deserializer for Layer JSON in legacy format - see BaseLegacyDeserializer
- LegacyLayerDeserializer() - Constructor for class org.deeplearning4j.nn.conf.serde.legacyformat.LegacyLayerDeserializer
-
- LegacyLayerDeserializerHelper - Class in org.deeplearning4j.nn.conf.serde.legacyformat
-
- LegacyPreprocessorDeserializer - Class in org.deeplearning4j.nn.conf.serde.legacyformat
-
Deserializer for InputPreProcessor JSON in legacy format - see BaseLegacyDeserializer
- LegacyPreprocessorDeserializer() - Constructor for class org.deeplearning4j.nn.conf.serde.legacyformat.LegacyPreprocessorDeserializer
-
- LegacyPreprocessorDeserializerHelper - Class in org.deeplearning4j.nn.conf.serde.legacyformat
-
- LegacyReconstructionDistributionDeserializer - Class in org.deeplearning4j.nn.conf.serde.legacyformat
-
Deserializer for ReconstructionDistribution JSON in legacy format - see BaseLegacyDeserializer
- LegacyReconstructionDistributionDeserializer() - Constructor for class org.deeplearning4j.nn.conf.serde.legacyformat.LegacyReconstructionDistributionDeserializer
-
- LegacyReconstructionDistributionDeserializerHelper - Class in org.deeplearning4j.nn.conf.serde.legacyformat
-
- len - Variable in class org.ansj.app.crf.pojo.Element
-
- LeNet - Class in org.deeplearning4j.zoo.model
-
LeNet was an early promising achiever on the ImageNet dataset.
- length(byte[]) - Static method in class org.deeplearning4j.ui.stats.impl.SbeUtil
-
- length(byte[][]) - Static method in class org.deeplearning4j.ui.stats.impl.SbeUtil
-
- length(byte[][][]) - Static method in class org.deeplearning4j.ui.stats.impl.SbeUtil
-
- length(String) - Static method in class org.deeplearning4j.ui.stats.impl.SbeUtil
-
- length(String[]) - Static method in class org.deeplearning4j.ui.stats.impl.SbeUtil
-
- length() - Method in class org.deeplearning4j.ui.stats.sbe.VarDataUTF8Decoder
-
- length(long) - Method in class org.deeplearning4j.ui.stats.sbe.VarDataUTF8Encoder
-
- lengthMaxValue() - Static method in class org.deeplearning4j.ui.stats.sbe.VarDataUTF8Decoder
-
- lengthMaxValue() - Static method in class org.deeplearning4j.ui.stats.sbe.VarDataUTF8Encoder
-
- lengthMinValue() - Static method in class org.deeplearning4j.ui.stats.sbe.VarDataUTF8Decoder
-
- lengthMinValue() - Static method in class org.deeplearning4j.ui.stats.sbe.VarDataUTF8Encoder
-
- lengthNullValue() - Static method in class org.deeplearning4j.ui.stats.sbe.VarDataUTF8Decoder
-
- lengthNullValue() - Static method in class org.deeplearning4j.ui.stats.sbe.VarDataUTF8Encoder
-
- LengthUnit - Enum in org.deeplearning4j.ui.api
-
LengthUnit: an enum for specifying units for things such as width and height
- LESS - Static variable in class org.deeplearning4j.clustering.kdtree.KDTree
-
- leverageTo(String) - Method in class org.deeplearning4j.nn.layers.recurrent.FwdPassReturn
-
This method is OPTIONAL, and written mostly for future use
- leverageTo(ArrayType, INDArray) - Method in class org.deeplearning4j.nn.workspace.LayerWorkspaceMgr
-
- LFWDataSetIterator - Class in org.deeplearning4j.datasets.iterator.impl
-
- LFWDataSetIterator(int[]) - Constructor for class org.deeplearning4j.datasets.iterator.impl.LFWDataSetIterator
-
Loads subset of images with given imgDim returned by the generator.
- LFWDataSetIterator(int, int) - Constructor for class org.deeplearning4j.datasets.iterator.impl.LFWDataSetIterator
-
Loads images with given batchSize, numExamples returned by the generator.
- LFWDataSetIterator(int, int, int[]) - Constructor for class org.deeplearning4j.datasets.iterator.impl.LFWDataSetIterator
-
Loads images with given batchSize, numExamples, imgDim returned by the generator.
- LFWDataSetIterator(int, int[], boolean) - Constructor for class org.deeplearning4j.datasets.iterator.impl.LFWDataSetIterator
-
Loads images with given batchSize, imgDim, useSubset, returned by the generator.
- LFWDataSetIterator(int, int, int[], boolean, double) - Constructor for class org.deeplearning4j.datasets.iterator.impl.LFWDataSetIterator
-
Loads images with given batchSize, numExamples, imgDim, train, & splitTrainTest returned by the generator.
- LFWDataSetIterator(int, int, int, boolean, double) - Constructor for class org.deeplearning4j.datasets.iterator.impl.LFWDataSetIterator
-
Loads images with given batchSize, numExamples, numLabels, train, & splitTrainTest returned by the generator.
- LFWDataSetIterator(int, int, int[], int, boolean, boolean, double, Random) - Constructor for class org.deeplearning4j.datasets.iterator.impl.LFWDataSetIterator
-
Loads images with given batchSize, numExamples, imgDim, numLabels, useSubset, train, splitTrainTest & Random returned by the generator.
- LFWDataSetIterator(int, int, int[], int, boolean, PathLabelGenerator, boolean, double, Random) - Constructor for class org.deeplearning4j.datasets.iterator.impl.LFWDataSetIterator
-
Loads images with given batchSize, numExamples, imgDim, numLabels, useSubset, train, splitTrainTest & Random returned by the generator.
- LFWDataSetIterator(int, int, int[], int, boolean, PathLabelGenerator, boolean, double, ImageTransform, Random) - Constructor for class org.deeplearning4j.datasets.iterator.impl.LFWDataSetIterator
-
Create LFW data specific iterator
- LibraryException - Exception in org.ansj.exception
-
- LibraryException(Exception) - Constructor for exception org.ansj.exception.LibraryException
-
- LibraryException(String) - Constructor for exception org.ansj.exception.LibraryException
-
- limit - Variable in class org.deeplearning4j.ui.stats.sbe.StaticInfoDecoder
-
- limit() - Method in class org.deeplearning4j.ui.stats.sbe.StaticInfoDecoder
-
- limit(int) - Method in class org.deeplearning4j.ui.stats.sbe.StaticInfoDecoder
-
- limit - Variable in class org.deeplearning4j.ui.stats.sbe.StaticInfoEncoder
-
- limit() - Method in class org.deeplearning4j.ui.stats.sbe.StaticInfoEncoder
-
- limit(int) - Method in class org.deeplearning4j.ui.stats.sbe.StaticInfoEncoder
-
- limit - Variable in class org.deeplearning4j.ui.stats.sbe.StorageMetaDataDecoder
-
- limit() - Method in class org.deeplearning4j.ui.stats.sbe.StorageMetaDataDecoder
-
- limit(int) - Method in class org.deeplearning4j.ui.stats.sbe.StorageMetaDataDecoder
-
- limit - Variable in class org.deeplearning4j.ui.stats.sbe.StorageMetaDataEncoder
-
- limit() - Method in class org.deeplearning4j.ui.stats.sbe.StorageMetaDataEncoder
-
- limit(int) - Method in class org.deeplearning4j.ui.stats.sbe.StorageMetaDataEncoder
-
- limit - Variable in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder
-
- limit() - Method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder
-
- limit(int) - Method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder
-
- limit - Variable in class org.deeplearning4j.ui.stats.sbe.UpdateEncoder
-
- limit() - Method in class org.deeplearning4j.ui.stats.sbe.UpdateEncoder
-
- limit(int) - Method in class org.deeplearning4j.ui.stats.sbe.UpdateEncoder
-
- limitVocabularySize(int) - Method in class org.deeplearning4j.models.paragraphvectors.ParagraphVectors.Builder
-
This method sets vocabulary limit during construction.
- limitVocabularySize(int) - Method in class org.deeplearning4j.models.sequencevectors.SequenceVectors.Builder
-
This method sets vocabulary limit during construction.
- limitVocabularySize(int) - Method in class org.deeplearning4j.models.word2vec.Word2Vec.Builder
-
This method sets vocabulary limit during construction.
- LineGradientDescent - Class in org.deeplearning4j.optimize.solvers
-
Stochastic Gradient Descent with Line Search
- LineGradientDescent(NeuralNetConfiguration, StepFunction, Collection<TrainingListener>, Model) - Constructor for class org.deeplearning4j.optimize.solvers.LineGradientDescent
-
- LineGradientDescent(NeuralNetConfiguration, StepFunction, Collection<TrainingListener>, Collection<TerminationCondition>, Model) - Constructor for class org.deeplearning4j.optimize.solvers.LineGradientDescent
-
- lineMaximizer - Variable in class org.deeplearning4j.optimize.solvers.BaseOptimizer
-
- LineOptimizer - Interface in org.deeplearning4j.optimize.api
-
Line optimizer interface adapted from mallet
- LineSentenceIterator - Class in org.deeplearning4j.text.sentenceiterator
-
Each line is a sentence
- LineSentenceIterator(File) - Constructor for class org.deeplearning4j.text.sentenceiterator.LineSentenceIterator
-
- list - Variable in class org.deeplearning4j.clustering.vptree.VPTree.NodeBuilder
-
- list - Variable in class org.deeplearning4j.datasets.iterator.file.BaseFileIterator
-
- list() - Method in class org.deeplearning4j.nn.conf.NeuralNetConfiguration.Builder
-
Create a ListBuilder (for creating a MultiLayerConfiguration)
Usage:
- list(Layer...) - Method in class org.deeplearning4j.nn.conf.NeuralNetConfiguration.Builder
-
Create a ListBuilder (for creating a MultiLayerConfiguration) with the specified layers
Usage:
- listActiveClusterIds() - Method in class org.deeplearning4j.aws.emr.SparkEMRClient
-
List existing active cluster IDs
- listActiveClusterNames() - Method in class org.deeplearning4j.aws.emr.SparkEMRClient
-
Lists existing active clusters Names
- ListBuilder(NeuralNetConfiguration.Builder, Map<Integer, NeuralNetConfiguration.Builder>) - Constructor for class org.deeplearning4j.nn.conf.NeuralNetConfiguration.ListBuilder
-
- ListBuilder(NeuralNetConfiguration.Builder) - Constructor for class org.deeplearning4j.nn.conf.NeuralNetConfiguration.ListBuilder
-
- ListDataSetIterator<T extends org.nd4j.linalg.dataset.DataSet> - Class in org.deeplearning4j.datasets.iterator.impl
-
Wraps a data applyTransformToDestination collection
- ListDataSetIterator(Collection<T>, int) - Constructor for class org.deeplearning4j.datasets.iterator.impl.ListDataSetIterator
-
- ListDataSetIterator(Collection<T>) - Constructor for class org.deeplearning4j.datasets.iterator.impl.ListDataSetIterator
-
Initializes with a batch of 5
- listener(TrainingListener...) - Method in class org.deeplearning4j.optimize.Solver.Builder
-
- ListenerEvent - Enum in org.deeplearning4j.models.sequencevectors.enums
-
This enum defines possible events, when specific VectorsListener will be fired
- listeners - Variable in class org.deeplearning4j.nn.layers.normalization.BatchNormalization
-
- listeners(Collection<TrainingListener>) - Method in class org.deeplearning4j.optimize.Solver.Builder
-
- listeners - Variable in class org.deeplearning4j.parallelism.ParallelWrapper
-
- listeners - Variable in class org.deeplearning4j.spark.impl.paramavg.BaseTrainingMaster
-
- listeners - Variable in class org.deeplearning4j.ui.storage.BaseCollectionStatsStorage
-
- listObjects(String) - Method in class org.deeplearning4j.aws.s3.reader.S3Downloader
-
Simple way of retrieving the listings for a bucket
- listObjectsInFile(File) - Static method in class org.deeplearning4j.util.ModelSerializer
-
- listPaths(JavaSparkContext, String) - Static method in class org.deeplearning4j.spark.util.SparkUtils
-
List of the files in the given directory (path), as a JavaRDD<String>
- listPaths(JavaSparkContext, String, boolean) - Static method in class org.deeplearning4j.spark.util.SparkUtils
-
List of the files in the given directory (path), as a JavaRDD<String>
- ListSequenceConvertFunction<T extends SequenceElement> - Class in org.deeplearning4j.spark.models.sequencevectors.functions
-
Simple function to convert List to Sequence
- ListSequenceConvertFunction() - Constructor for class org.deeplearning4j.spark.models.sequencevectors.functions.ListSequenceConvertFunction
-
- listSessionIDs() - Method in interface org.deeplearning4j.api.storage.StatsStorage
-
Get a list of all sessions stored by this storage backend
- listSessionIDs() - Method in class org.deeplearning4j.ui.storage.BaseCollectionStatsStorage
-
- listSessionIDs() - Method in class org.deeplearning4j.ui.storage.sqlite.J7FileStatsStorage
-
- listToArray(List<Byte>) - Static method in class org.deeplearning4j.models.word2vec.wordstore.VocabularyHolder
-
- listToArray(List<Integer>, int) - Static method in class org.deeplearning4j.models.word2vec.wordstore.VocabularyHolder
-
- listTypeIDsForSession(String) - Method in interface org.deeplearning4j.api.storage.StatsStorage
-
Get the list of type IDs for the given session ID
- listTypeIDsForSession(String) - Method in class org.deeplearning4j.ui.storage.BaseCollectionStatsStorage
-
- listTypeIDsForSession(String) - Method in class org.deeplearning4j.ui.storage.sqlite.J7FileStatsStorage
-
- listWorkerIDsForSession(String) - Method in interface org.deeplearning4j.api.storage.StatsStorage
-
For a given session ID, list all of the known worker IDs
- listWorkerIDsForSession(String) - Method in class org.deeplearning4j.ui.storage.BaseCollectionStatsStorage
-
- listWorkerIDsForSession(String) - Method in class org.deeplearning4j.ui.storage.sqlite.J7FileStatsStorage
-
- listWorkerIDsForSessionAndType(String, String) - Method in interface org.deeplearning4j.api.storage.StatsStorage
-
For a given session ID and type ID, list all of the known worker IDs
- listWorkerIDsForSessionAndType(String, String) - Method in class org.deeplearning4j.ui.storage.BaseCollectionStatsStorage
-
- listWorkerIDsForSessionAndType(String, String) - Method in class org.deeplearning4j.ui.storage.sqlite.J7FileStatsStorage
-
- load(String) - Static method in class org.ansj.app.crf.Model
-
模型读取
- load(Class<? extends Model>, InputStream) - Static method in class org.ansj.app.crf.Model
-
模型读取
- load(File) - Method in class org.deeplearning4j.datasets.iterator.file.BaseFileIterator
-
- load(File) - Method in class org.deeplearning4j.datasets.iterator.file.FileDataSetIterator
-
- load(File) - Method in class org.deeplearning4j.datasets.iterator.file.FileMultiDataSetIterator
-
- load(InputStream, VocabCache<? extends SequenceElement>) - Static method in class org.deeplearning4j.models.glove.GloveWeightLookupTable
-
Deprecated.
Load a glove model from an input stream.
- load(InputStream) - Static method in class org.deeplearning4j.models.word2vec.wordstore.inmemory.InMemoryLookupCache
-
Deprecated.
Load a look up cache from an input stream
delimited by \n
- load(File, boolean) - Static method in class org.deeplearning4j.nn.graph.ComputationGraph
-
- load(File, boolean) - Static method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
-
- load(T) - Method in class org.deeplearning4j.spark.iterator.BaseDataSetIterator
-
- load(String) - Method in class org.deeplearning4j.spark.iterator.PathSparkDataSetIterator
-
- load(PortableDataStream) - Method in class org.deeplearning4j.spark.iterator.PortableDataStreamDataSetIterator
-
- loadCheckpointCG(Checkpoint) - Method in class org.deeplearning4j.optimize.listeners.checkpoint.CheckpointListener
-
Load a ComputationGraph for the given checkpoint
- loadCheckpointCG(int) - Method in class org.deeplearning4j.optimize.listeners.checkpoint.CheckpointListener
-
Load a ComputationGraph for the given checkpoint
- loadCheckpointMLN(Checkpoint) - Method in class org.deeplearning4j.optimize.listeners.checkpoint.CheckpointListener
-
Load a MultiLayerNetwork for the given checkpoint
- loadCheckpointMLN(int) - Method in class org.deeplearning4j.optimize.listeners.checkpoint.CheckpointListener
-
Load a MultiLayerNetwork for the given checkpoint number
- loadCodes(int[]) - Method in class org.deeplearning4j.models.embeddings.inmemory.InMemoryLookupTable
-
Loads the co-occurrences for the given codes
- loadCodes(int[]) - Method in interface org.deeplearning4j.models.embeddings.WeightLookupTable
-
Loads the co-occurrences for the given codes
- loadConfigGuess(String) - Static method in class org.deeplearning4j.util.ModelGuesser
-
Load the model from the given file path
- loadConfigGuess(InputStream) - Static method in class org.deeplearning4j.util.ModelGuesser
-
Load the model from the given input stream
- loadDictionaries() - Method in class com.atilika.kuromoji.ipadic.Tokenizer.Builder
-
- loadDictionaries() - Method in class com.atilika.kuromoji.TokenizerBase.Builder
-
- loader - Variable in class org.deeplearning4j.datasets.iterator.impl.CifarDataSetIterator
-
- loadFromMetaData(RecordMetaData) - Method in class org.deeplearning4j.datasets.datavec.RecordReaderDataSetIterator
-
Load a single example to a DataSet, using the provided RecordMetaData.
- loadFromMetaData(List<RecordMetaData>) - Method in class org.deeplearning4j.datasets.datavec.RecordReaderDataSetIterator
-
Load a multiple examples to a DataSet, using the provided RecordMetaData instances.
- loadFromMetaData(RecordMetaData) - Method in class org.deeplearning4j.datasets.datavec.RecordReaderMultiDataSetIterator
-
Load a single example to a DataSet, using the provided RecordMetaData.
- loadFromMetaData(List<RecordMetaData>) - Method in class org.deeplearning4j.datasets.datavec.RecordReaderMultiDataSetIterator
-
Load a multiple sequence examples to a DataSet, using the provided RecordMetaData instances.
- loadFromMetaData(RecordMetaData) - Method in class org.deeplearning4j.datasets.datavec.SequenceRecordReaderDataSetIterator
-
Load a single sequence example to a DataSet, using the provided RecordMetaData.
- loadFromMetaData(List<RecordMetaData>) - Method in class org.deeplearning4j.datasets.datavec.SequenceRecordReaderDataSetIterator
-
Load a multiple sequence examples to a DataSet, using the provided RecordMetaData instances.
- loadFromMetaData(RecordMetaData) - Method in class org.deeplearning4j.spark.datavec.iterator.SparkSourceDummyReader
-
- loadFromMetaData(List<RecordMetaData>) - Method in class org.deeplearning4j.spark.datavec.iterator.SparkSourceDummyReader
-
- loadFullModel(String) - Static method in class org.deeplearning4j.models.embeddings.loader.WordVectorSerializer
-
Deprecated.
- loadGraph(String, EdgeLineProcessor<E>, VertexFactory<V>, int, boolean) - Static method in class org.deeplearning4j.graph.data.GraphLoader
-
Load a graph into memory, using a given EdgeLineProcessor.
- loadGraph(String, String, VertexLoader<V>, EdgeLineProcessor<E>, boolean) - Static method in class org.deeplearning4j.graph.data.GraphLoader
-
Load graph, assuming vertices are in one file and edges are in another file.
- loadIris(int, int) - Static method in class org.deeplearning4j.base.IrisUtils
-
- loadModel(String) - Method in class org.ansj.app.crf.model.CRFModel
-
- loadModel(InputStream) - Method in class org.ansj.app.crf.model.CRFModel
-
- loadModel(String) - Method in class org.ansj.app.crf.model.CRFppTxtModel
-
解析crf++生成的可可视txt文件
- loadModel(InputStream) - Method in class org.ansj.app.crf.model.CRFppTxtModel
-
- loadModel(String) - Method in class org.ansj.app.crf.Model
-
不同的模型实现自己的加载模型类
- loadModel(InputStream) - Method in class org.ansj.app.crf.Model
-
- loadModel(String) - Method in class org.ansj.app.crf.model.WapitiCRFModel
-
- loadModel(InputStream) - Method in class org.ansj.app.crf.model.WapitiCRFModel
-
- loadModelGuess(String) - Static method in class org.deeplearning4j.util.ModelGuesser
-
Load the model from the given file path
- loadModelGuess(InputStream) - Static method in class org.deeplearning4j.util.ModelGuesser
-
Load the model from the given input stream
- loadModelGuess(InputStream, File) - Static method in class org.deeplearning4j.util.ModelGuesser
-
Deprecated.
- loadNormalizer(InputStream) - Static method in class org.deeplearning4j.util.ModelGuesser
-
- loadNormalizer(String) - Static method in class org.deeplearning4j.util.ModelGuesser
-
- loadSequenceFromMetaData(RecordMetaData) - Method in class org.deeplearning4j.spark.datavec.iterator.SparkSourceDummySeqReader
-
- loadSequenceFromMetaData(List<RecordMetaData>) - Method in class org.deeplearning4j.spark.datavec.iterator.SparkSourceDummySeqReader
-
- LoadSerializedDataSetFunction - Class in org.deeplearning4j.spark.impl.common
-
This is a function that is used to load a DataSet object using DataSet.load(InputStream).
- LoadSerializedDataSetFunction() - Constructor for class org.deeplearning4j.spark.impl.common.LoadSerializedDataSetFunction
-
- loadSingleSentence(String) - Method in class org.deeplearning4j.iterator.CnnSentenceDataSetIterator
-
Generally used post training time to load a single sentence for predictions
- loadStaticModel(File) - Static method in class org.deeplearning4j.models.embeddings.loader.WordVectorSerializer
-
This method restores previously saved w2v model.
- loadTxt(File) - Static method in class org.deeplearning4j.models.embeddings.loader.WordVectorSerializer
-
Loads an in memory cache from the given path (sets syn0 and the vocab)
- loadTxtVectors(File) - Static method in class org.deeplearning4j.graph.models.loader.GraphVectorSerializer
-
- loadTxtVectors(File) - Static method in class org.deeplearning4j.models.embeddings.loader.WordVectorSerializer
-
Deprecated.
- loadTxtVectors(InputStream, boolean) - Static method in class org.deeplearning4j.models.embeddings.loader.WordVectorSerializer
-
Deprecated.
- loadUndirectedGraphEdgeListFile(String, int, String) - Static method in class org.deeplearning4j.graph.data.GraphLoader
-
Simple method for loading an undirected graph, where the graph is represented by a edge list with one edge
per line with a delimiter in between
This method assumes that all lines in the file are of the form
i<delim>j where i and j are integers
in range 0 to numVertices inclusive, and "
" is the user-provided delimiter
Note: this method calls GraphLoader.loadUndirectedGraphEdgeListFile(String, int, String, boolean) with allowMultipleEdges = true.
- loadUndirectedGraphEdgeListFile(String, int, String, boolean) - Static method in class org.deeplearning4j.graph.data.GraphLoader
-
Simple method for loading an undirected graph, where the graph is represented by a edge list with one edge
per line with a delimiter in between
This method assumes that all lines in the file are of the form i<delim>j where i and j are integers
in range 0 to numVertices inclusive, and "" is the user-provided delimiter
- loadVertices(String) - Method in class org.deeplearning4j.graph.data.impl.DelimitedVertexLoader
-
- loadVertices(String) - Method in interface org.deeplearning4j.graph.data.VertexLoader
-
- loadVocab() - Method in class org.deeplearning4j.models.word2vec.wordstore.inmemory.AbstractCache
-
Deserialize vocabulary from specified path
- loadVocab() - Method in class org.deeplearning4j.models.word2vec.wordstore.inmemory.InMemoryLookupCache
-
Deprecated.
- loadVocab() - Method in interface org.deeplearning4j.models.word2vec.wordstore.VocabCache
-
Load vocab
- loadWeightedEdgeListFile(String, int, String, boolean, String...) - Static method in class org.deeplearning4j.graph.data.GraphLoader
-
Method for loading a weighted graph from an edge list file, where each edge (inc.
- loadWeightedEdgeListFile(String, int, String, boolean, boolean, String...) - Static method in class org.deeplearning4j.graph.data.GraphLoader
-
Method for loading a weighted graph from an edge list file, where each edge (inc.
- LOCAL_CACHE - Variable in class org.deeplearning4j.datasets.fetchers.CacheableExtractableDataSetFetcher
-
- LOCAL_DIR_NAME - Static variable in class org.deeplearning4j.base.EmnistFetcher
-
- LOCAL_DIR_NAME - Static variable in class org.deeplearning4j.base.MnistFetcher
-
- localCacheName() - Method in class org.deeplearning4j.datasets.fetchers.SvhnDataFetcher
-
- localCacheName() - Method in class org.deeplearning4j.datasets.fetchers.TinyImageNetFetcher
-
- localCacheName() - Method in class org.deeplearning4j.datasets.fetchers.UciSequenceDataFetcher
-
- LocalFileGraphSaver - Class in org.deeplearning4j.earlystopping.saver
-
Save the best (and latest/most recent)
ComputationGraphs learned during early stopping training to the local file system.
Instances of this class will save 3 files for best (and optionally, latest) models:
(a) The network configuration: bestGraphConf.json
(b) The network parameters: bestGraphParams.bin
(c) The network updater: bestGraphUpdater.bin
NOTE: The model updater is an object that contains the internal state for training features such as AdaGrad, Momentum
and RMSProp.
The updater is
not required to use the network at test time; it is saved in case further training is required.
- LocalFileGraphSaver(String) - Constructor for class org.deeplearning4j.earlystopping.saver.LocalFileGraphSaver
-
Constructor that uses default character set for configuration (json) encoding
- LocalFileGraphSaver(String, Charset) - Constructor for class org.deeplearning4j.earlystopping.saver.LocalFileGraphSaver
-
- LocalFileModelSaver - Class in org.deeplearning4j.earlystopping.saver
-
Save the best (and latest/most recent) models learned during early stopping training to the local file system.
Instances of this class will save 3 files for best (and optionally, latest) models:
(a) The network configuration: bestModelConf.json
(b) The network parameters: bestModelParams.bin
(c) The network updater: bestModelUpdater.bin
NOTE: The model updater is an object that contains the internal state for training features such as AdaGrad, Momentum
and RMSProp.
The updater is not required to use the network at test time; it is saved in case further training is required.
- LocalFileModelSaver(String) - Constructor for class org.deeplearning4j.earlystopping.saver.LocalFileModelSaver
-
Constructor that uses default character set for configuration (json) encoding
- LocalFileModelSaver(String, Charset) - Constructor for class org.deeplearning4j.earlystopping.saver.LocalFileModelSaver
-
- LocalHandler - Class in org.deeplearning4j.optimize.solvers.accumulation
-
MessageHandler implementation suited for ParallelWrapper running on single box
PLEASE NOTE: This handler does NOT provide any network connectivity.
- LocalHandler() - Constructor for class org.deeplearning4j.optimize.solvers.accumulation.LocalHandler
-
- localIp - Variable in class org.deeplearning4j.spark.parameterserver.networking.messages.SilentIntroductoryMessage
-
- LocalResponseNormalization - Class in org.deeplearning4j.nn.conf.layers
-
Created by nyghtowl on 10/29/15.
- LocalResponseNormalization - Class in org.deeplearning4j.nn.layers.normalization
-
Deep neural net normalization approach normalizes activations between layers
"brightness normalization"
Used for nets like AlexNet
- LocalResponseNormalization(NeuralNetConfiguration, INDArray) - Constructor for class org.deeplearning4j.nn.layers.normalization.LocalResponseNormalization
-
- LocalResponseNormalization(NeuralNetConfiguration) - Constructor for class org.deeplearning4j.nn.layers.normalization.LocalResponseNormalization
-
- LocalResponseNormalization.Builder - Class in org.deeplearning4j.nn.conf.layers
-
- LocalResponseNormalizationHelper - Interface in org.deeplearning4j.nn.layers.normalization
-
Helper for the local response normalization layer.
- LocalUnstructuredDataFormatter - Class in org.deeplearning4j.datasets.rearrange
-
Rearrange an unstructured dataset
in to split test/train
on the file system
- LocalUnstructuredDataFormatter(File, File, LocalUnstructuredDataFormatter.LabelingType, double) - Constructor for class org.deeplearning4j.datasets.rearrange.LocalUnstructuredDataFormatter
-
- LocalUnstructuredDataFormatter.LabelingType - Enum in org.deeplearning4j.datasets.rearrange
-
- lock - Variable in class org.deeplearning4j.models.glove.AbstractCoOccurrences
-
- lock - Variable in class org.deeplearning4j.optimize.solvers.accumulation.FancyBlockingQueue
-
- lockGammaBeta - Variable in class org.deeplearning4j.nn.conf.layers.BatchNormalization.Builder
-
- lockGammaBeta(boolean) - Method in class org.deeplearning4j.nn.conf.layers.BatchNormalization.Builder
-
- lockGammaBeta - Variable in class org.deeplearning4j.nn.conf.layers.BatchNormalization
-
- locks - Variable in class org.deeplearning4j.optimize.solvers.accumulation.EncodedGradientsAccumulator
-
- log - Static variable in class com.atilika.kuromoji.util.FileResourceResolver
-
- LOG - Static variable in class org.ansj.util.MyStaticValue
-
- log - Static variable in class org.deeplearning4j.base.MnistFetcher
-
- log - Static variable in class org.deeplearning4j.datasets.iterator.MultipleEpochsIterator
-
Deprecated.
- log - Static variable in class org.deeplearning4j.models.sequencevectors.SequenceVectors
-
- log - Static variable in class org.deeplearning4j.models.sequencevectors.serialization.AbstractElementFactory
-
- log - Static variable in class org.deeplearning4j.models.sequencevectors.transformers.impl.GraphTransformer
-
- log - Static variable in class org.deeplearning4j.models.sequencevectors.transformers.impl.SentenceTransformer
-
- log - Static variable in class org.deeplearning4j.models.word2vec.wordstore.VocabConstructor
-
- log - Static variable in class org.deeplearning4j.nn.layers.convolution.ConvolutionLayer
-
- log - Static variable in class org.deeplearning4j.nn.layers.normalization.LocalResponseNormalization
-
- log - Static variable in class org.deeplearning4j.optimize.solvers.BaseOptimizer
-
- log - Static variable in class org.deeplearning4j.text.sentenceiterator.interoperability.SentenceIteratorConverter
-
- log - Static variable in class org.deeplearning4j.text.sentenceiterator.PrefetchingSentenceIterator
-
Deprecated.
- log - Static variable in class org.deeplearning4j.text.tokenization.tokenizer.DefaultStreamTokenizer
-
- log2 - Static variable in class org.deeplearning4j.clustering.util.MathUtils
-
The natural logarithm of 2.
- log2(double) - Static method in class org.deeplearning4j.clustering.util.MathUtils
-
Returns the logarithm of a for base 2.
- logAggregateStartTime() - Method in class org.deeplearning4j.spark.impl.paramavg.stats.ParameterAveragingTrainingMasterStats.ParameterAveragingTrainingMasterStatsHelper
-
- logAggregationEndTime() - Method in class org.deeplearning4j.spark.impl.paramavg.stats.ParameterAveragingTrainingMasterStats.ParameterAveragingTrainingMasterStatsHelper
-
- logBroadcastEnd() - Method in class org.deeplearning4j.spark.impl.paramavg.stats.ParameterAveragingTrainingMasterStats.ParameterAveragingTrainingMasterStatsHelper
-
- logBroadcastGetValueEnd() - Method in class org.deeplearning4j.spark.impl.paramavg.stats.ParameterAveragingTrainingWorkerStats.ParameterAveragingTrainingWorkerStatsHelper
-
- logBroadcastGetValueStart() - Method in class org.deeplearning4j.spark.impl.paramavg.stats.ParameterAveragingTrainingWorkerStats.ParameterAveragingTrainingWorkerStatsHelper
-
- logBroadcastStart() - Method in class org.deeplearning4j.spark.impl.paramavg.stats.ParameterAveragingTrainingMasterStats.ParameterAveragingTrainingMasterStatsHelper
-
- logCountEnd() - Method in class org.deeplearning4j.spark.impl.paramavg.stats.ParameterAveragingTrainingMasterStats.ParameterAveragingTrainingMasterStatsHelper
-
- logCountStart() - Method in class org.deeplearning4j.spark.impl.paramavg.stats.ParameterAveragingTrainingMasterStats.ParameterAveragingTrainingMasterStatsHelper
-
- logExportEnd() - Method in class org.deeplearning4j.spark.impl.paramavg.stats.ParameterAveragingTrainingMasterStats.ParameterAveragingTrainingMasterStatsHelper
-
- logExportStart() - Method in class org.deeplearning4j.spark.impl.paramavg.stats.ParameterAveragingTrainingMasterStats.ParameterAveragingTrainingMasterStatsHelper
-
- logFitEnd(int) - Method in class org.deeplearning4j.spark.impl.paramavg.stats.ParameterAveragingTrainingMasterStats.ParameterAveragingTrainingMasterStatsHelper
-
- logFitEnd(int) - Method in class org.deeplearning4j.spark.impl.paramavg.stats.ParameterAveragingTrainingWorkerStats.ParameterAveragingTrainingWorkerStatsHelper
-
- logFitStart() - Method in class org.deeplearning4j.spark.impl.paramavg.stats.ParameterAveragingTrainingMasterStats.ParameterAveragingTrainingMasterStatsHelper
-
- logFitStart() - Method in class org.deeplearning4j.spark.impl.paramavg.stats.ParameterAveragingTrainingWorkerStats.ParameterAveragingTrainingWorkerStatsHelper
-
- logger - Static variable in class org.ansj.app.crf.Model
-
- logger - Static variable in class org.ansj.recognition.arrimpl.UserDefineRecognition
-
- logger - Static variable in class org.deeplearning4j.models.glove.AbstractCoOccurrences
-
- logger - Static variable in class org.deeplearning4j.models.glove.count.BinaryCoOccurrenceReader
-
- logger - Static variable in class org.deeplearning4j.models.sequencevectors.listeners.ScoreListener
-
Deprecated.
- logger - Static variable in class org.deeplearning4j.models.sequencevectors.listeners.SimilarityListener
-
- logger - Static variable in class org.deeplearning4j.plot.Tsne
-
- logger - Variable in class org.deeplearning4j.text.sentenceiterator.StreamLineIterator
-
- logInitEnd() - Method in class org.deeplearning4j.spark.impl.paramavg.stats.ParameterAveragingTrainingWorkerStats.ParameterAveragingTrainingWorkerStatsHelper
-
- logInitialModelAfter() - Method in class org.deeplearning4j.spark.api.stats.StatsCalculationHelper
-
- logInitialModelBefore() - Method in class org.deeplearning4j.spark.api.stats.StatsCalculationHelper
-
- logMapPartitionsEnd(int) - Method in class org.deeplearning4j.spark.impl.paramavg.stats.ParameterAveragingTrainingMasterStats.ParameterAveragingTrainingMasterStatsHelper
-
- logMapPartitionsStart() - Method in class org.deeplearning4j.spark.impl.paramavg.stats.ParameterAveragingTrainingMasterStats.ParameterAveragingTrainingMasterStatsHelper
-
- logMethodStartTime() - Method in class org.deeplearning4j.spark.api.stats.StatsCalculationHelper
-
- logNextDataSetAfter(int) - Method in class org.deeplearning4j.spark.api.stats.StatsCalculationHelper
-
- logNextDataSetBefore() - Method in class org.deeplearning4j.spark.api.stats.StatsCalculationHelper
-
- LogNormalDistribution - Class in org.deeplearning4j.nn.conf.distribution
-
A log-normal distribution.
- LogNormalDistribution(double, double) - Constructor for class org.deeplearning4j.nn.conf.distribution.LogNormalDistribution
-
Create a log-normal distribution
with the given mean and std
- logProb - Variable in class org.deeplearning4j.earlystopping.scorecalc.VAEReconProbScoreCalculator
-
- logProcessMinibatchAfter() - Method in class org.deeplearning4j.spark.api.stats.StatsCalculationHelper
-
- logProcessMinibatchBefore() - Method in class org.deeplearning4j.spark.api.stats.StatsCalculationHelper
-
- logProcessParamsUpdaterEnd() - Method in class org.deeplearning4j.spark.impl.paramavg.stats.ParameterAveragingTrainingMasterStats.ParameterAveragingTrainingMasterStatsHelper
-
- logProcessParamsUpdaterStart() - Method in class org.deeplearning4j.spark.impl.paramavg.stats.ParameterAveragingTrainingMasterStats.ParameterAveragingTrainingMasterStatsHelper
-
- logRepartitionEnd() - Method in class org.deeplearning4j.spark.impl.paramavg.stats.ParameterAveragingTrainingMasterStats.ParameterAveragingTrainingMasterStatsHelper
-
- logRepartitionStart() - Method in class org.deeplearning4j.spark.impl.paramavg.stats.ParameterAveragingTrainingMasterStats.ParameterAveragingTrainingMasterStatsHelper
-
- logReturnTime() - Method in class org.deeplearning4j.spark.api.stats.StatsCalculationHelper
-
- logs2probs(double[]) - Static method in class org.deeplearning4j.clustering.util.MathUtils
-
Converts an array containing the natural logarithms of
probabilities stored in a vector back into probabilities.
- logSaving(boolean) - Method in class org.deeplearning4j.optimize.listeners.checkpoint.CheckpointListener.Builder
-
If true (the default) log a message every time a model is saved
- logSplitEnd() - Method in class org.deeplearning4j.spark.impl.paramavg.stats.ParameterAveragingTrainingMasterStats.ParameterAveragingTrainingMasterStatsHelper
-
- logSplitStart() - Method in class org.deeplearning4j.spark.impl.paramavg.stats.ParameterAveragingTrainingMasterStats.ParameterAveragingTrainingMasterStatsHelper
-
- logTestMode(boolean) - Method in class org.deeplearning4j.nn.layers.FrozenLayer
-
- logTestMode(Layer.TrainingMode) - Method in class org.deeplearning4j.nn.layers.FrozenLayer
-
- logTestMode(boolean) - Method in class org.deeplearning4j.nn.layers.FrozenLayerWithBackprop
-
- logTestMode(Layer.TrainingMode) - Method in class org.deeplearning4j.nn.layers.FrozenLayerWithBackprop
-
- lookUp(int) - Method in class com.atilika.kuromoji.buffer.WordIdMap
-
- lookup(String) - Method in class com.atilika.kuromoji.trie.DoubleArrayTrie
-
Match input keyword.
- lookup(String, int, int) - Method in class com.atilika.kuromoji.trie.DoubleArrayTrie
-
- lookupCategories(char) - Method in class com.atilika.kuromoji.dict.CharacterDefinitions
-
- lookupDefinition(int) - Method in class com.atilika.kuromoji.dict.CharacterDefinitions
-
- lookupEntry(int) - Method in class com.atilika.kuromoji.buffer.TokenInfoBuffer
-
- lookupFeature(int, int) - Method in class com.atilika.kuromoji.buffer.TokenInfoBuffer
-
- lookupPartOfSpeechFeature(int, int) - Method in class com.atilika.kuromoji.buffer.TokenInfoBuffer
-
- lookupTable() - Method in class org.deeplearning4j.graph.models.deepwalk.DeepWalk
-
- lookupTable - Variable in class org.deeplearning4j.graph.models.embeddings.GraphVectorsImpl
-
- lookupTable - Variable in class org.deeplearning4j.models.embeddings.learning.impl.elements.SkipGram
-
- lookupTable - Variable in class org.deeplearning4j.models.embeddings.learning.impl.sequence.DBOW
-
- lookupTable - Variable in class org.deeplearning4j.models.embeddings.reader.impl.BasicModelUtils
-
- lookupTable() - Method in interface org.deeplearning4j.models.embeddings.wordvectors.WordVectors
-
Lookup table for the vectors
- lookupTable - Variable in class org.deeplearning4j.models.embeddings.wordvectors.WordVectorsImpl
-
- lookupTable() - Method in class org.deeplearning4j.models.embeddings.wordvectors.WordVectorsImpl
-
- lookupTable(WeightLookupTable<VocabWord>) - Method in class org.deeplearning4j.models.glove.Glove.Builder
-
- lookupTable(WeightLookupTable<V>) - Method in class org.deeplearning4j.models.node2vec.Node2Vec.Builder
-
Deprecated.
- lookupTable(WeightLookupTable<VocabWord>) - Method in class org.deeplearning4j.models.paragraphvectors.ParagraphVectors.Builder
-
This method allows to define external WeightLookupTable to be used
- lookupTable - Variable in class org.deeplearning4j.models.sequencevectors.SequenceVectors.Builder
-
- lookupTable(WeightLookupTable<T>) - Method in class org.deeplearning4j.models.sequencevectors.SequenceVectors.Builder
-
You can pass externally built WeightLookupTable, containing model weights and vocabulary.
- lookupTable() - Method in class org.deeplearning4j.models.word2vec.StaticWord2Vec
-
Lookup table for the vectors
PLEASE NOTE: This method is not available in this implementation.
- lookupTable(WeightLookupTable<VocabWord>) - Method in class org.deeplearning4j.models.word2vec.Word2Vec.Builder
-
This method allows to define external WeightLookupTable to be used
- lookupTable - Variable in class org.deeplearning4j.spark.models.sequencevectors.export.impl.VocabCacheExporter
-
- lookupTokenInfo(int, int) - Method in class com.atilika.kuromoji.buffer.TokenInfoBuffer
-
- lookupWordIds(int) - Method in class com.atilika.kuromoji.dict.TokenInfoDictionary
-
- lookupWordIds(int) - Method in class com.atilika.kuromoji.dict.UnknownDictionary
-
- lossClassPredictions(ILossFunction) - Method in class org.deeplearning4j.nn.conf.layers.objdetect.Yolo2OutputLayer.Builder
-
Loss function for the class predictions - defaults to L2 loss (i.e., sum of squared errors, as per the
paper), however Loss MCXENT could also be used (which is more common for classification).
- lossFn - Variable in class org.deeplearning4j.nn.conf.layers.BaseOutputLayer.Builder
-
- lossFn - Variable in class org.deeplearning4j.nn.conf.layers.BaseOutputLayer
-
- lossFn - Variable in class org.deeplearning4j.nn.conf.layers.CnnLossLayer
-
- lossFn - Variable in class org.deeplearning4j.nn.conf.layers.LossLayer
-
- lossFn - Variable in class org.deeplearning4j.nn.conf.layers.RnnLossLayer
-
- lossFunction(LossFunctions.LossFunction) - Method in class org.deeplearning4j.nn.conf.layers.BaseOutputLayer.Builder
-
- lossFunction(ILossFunction) - Method in class org.deeplearning4j.nn.conf.layers.BaseOutputLayer.Builder
-
- lossFunction - Variable in class org.deeplearning4j.nn.conf.layers.BasePretrainNetwork.Builder
-
- lossFunction(LossFunctions.LossFunction) - Method in class org.deeplearning4j.nn.conf.layers.BasePretrainNetwork.Builder
-
- lossFunction - Variable in class org.deeplearning4j.nn.conf.layers.BasePretrainNetwork
-
- lossFunction(IActivation, LossFunctions.LossFunction) - Method in class org.deeplearning4j.nn.conf.layers.variational.VariationalAutoencoder.Builder
-
Configure the VAE to use the specified loss function for the reconstruction, instead of a ReconstructionDistribution.
- lossFunction(Activation, LossFunctions.LossFunction) - Method in class org.deeplearning4j.nn.conf.layers.variational.VariationalAutoencoder.Builder
-
Configure the VAE to use the specified loss function for the reconstruction, instead of a ReconstructionDistribution.
- lossFunction(IActivation, ILossFunction) - Method in class org.deeplearning4j.nn.conf.layers.variational.VariationalAutoencoder.Builder
-
Configure the VAE to use the specified loss function for the reconstruction, instead of a ReconstructionDistribution.
- LossFunctionWrapper - Class in org.deeplearning4j.nn.conf.layers.variational
-
LossFunctionWrapper allows training of a VAE model with a standard (possibly deterministic) neural network loss function
for the reconstruction, instead of using a
ReconstructionDistribution as would normally be done with a VAE model.
- LossFunctionWrapper(IActivation, ILossFunction) - Constructor for class org.deeplearning4j.nn.conf.layers.variational.LossFunctionWrapper
-
- LossFunctionWrapper(Activation, ILossFunction) - Constructor for class org.deeplearning4j.nn.conf.layers.variational.LossFunctionWrapper
-
- LossLayer - Class in org.deeplearning4j.nn.conf.layers
-
LossLayer is a flexible output "layer" that performs a loss function on
an input without MLP logic.
- LossLayer(LossLayer.Builder) - Constructor for class org.deeplearning4j.nn.conf.layers.LossLayer
-
- LossLayer - Class in org.deeplearning4j.nn.layers
-
LossLayer is a flexible output "layer" that performs a loss function on
an input without MLP logic.
- LossLayer(NeuralNetConfiguration) - Constructor for class org.deeplearning4j.nn.layers.LossLayer
-
- LossLayer(NeuralNetConfiguration, INDArray) - Constructor for class org.deeplearning4j.nn.layers.LossLayer
-
- LossLayer.Builder - Class in org.deeplearning4j.nn.conf.layers
-
- lossPositionScale(ILossFunction) - Method in class org.deeplearning4j.nn.conf.layers.objdetect.Yolo2OutputLayer.Builder
-
Loss function for position/scale component of the loss function
- LowCasePreProcessor - Class in org.deeplearning4j.text.tokenization.tokenizer.preprocessor
-
- LowCasePreProcessor() - Constructor for class org.deeplearning4j.text.tokenization.tokenizer.preprocessor.LowCasePreProcessor
-
- lr - Variable in class org.deeplearning4j.models.embeddings.inmemory.InMemoryLookupTable.Builder
-
- lr(double) - Method in class org.deeplearning4j.models.embeddings.inmemory.InMemoryLookupTable.Builder
-
Deprecated.
- lr - Variable in class org.deeplearning4j.models.embeddings.inmemory.InMemoryLookupTable
-
- lr(double) - Method in class org.deeplearning4j.models.glove.GloveWeightLookupTable.Builder
-
Deprecated.
- lr(double) - Method in class org.deeplearning4j.spark.models.embeddings.glove.GloveParam.Builder
-
- LSH - Interface in org.deeplearning4j.clustering.lsh
-
This interface gathers the minimal elements for an LSH implementation
See chapter 3 of :
_Mining Massive Datasets_, Anand Rajaraman and Jeffrey Ullman
http://www.mmds.org/
- LSTM - Class in org.deeplearning4j.nn.conf.layers
-
LSTM recurrent net without peephole connections.
- LSTM - Class in org.deeplearning4j.nn.layers.recurrent
-
LSTM layer implementation.
- LSTM(NeuralNetConfiguration) - Constructor for class org.deeplearning4j.nn.layers.recurrent.LSTM
-
- LSTM(NeuralNetConfiguration, INDArray) - Constructor for class org.deeplearning4j.nn.layers.recurrent.LSTM
-
- LSTM.Builder - Class in org.deeplearning4j.nn.conf.layers
-
- LSTMHelper - Interface in org.deeplearning4j.nn.layers.recurrent
-
Helper for the recurrent LSTM layer (no peephole connections).
- LSTMHelpers - Class in org.deeplearning4j.nn.layers.recurrent
-
RNN tutorial: http://deeplearning4j.org/usingrnns.html
READ THIS FIRST if you want to understand what the heck is happening here.
- LSTMParamInitializer - Class in org.deeplearning4j.nn.params
-
LSTM Parameter initializer, for LSTM based on
Graves: Supervised Sequence Labelling with Recurrent Neural Networks
http://www.cs.toronto.edu/~graves/phd.pdf
- LSTMParamInitializer() - Constructor for class org.deeplearning4j.nn.params.LSTMParamInitializer
-
- lt(DataSet, DataSet) - Method in class org.deeplearning4j.spark.ordering.DataSetOrdering
-
- lteq(DataSet, DataSet) - Method in class org.deeplearning4j.spark.ordering.DataSetOrdering
-
- M - Static variable in class org.ansj.app.crf.Config
-
- M - Static variable in class org.ansj.domain.TermNature
-
系统内置的几个
- M - Static variable in class org.ansj.domain.TermNatures
-
- machineId - Variable in class org.deeplearning4j.spark.stats.BaseEventStats
-
- MagicQueue<T> - Class in org.deeplearning4j.parallelism
-
Deprecated.
- MagicQueue(int, int, MagicQueue.Type) - Constructor for class org.deeplearning4j.parallelism.MagicQueue
-
Deprecated.
- MagicQueue.Builder - Class in org.deeplearning4j.parallelism
-
Deprecated.
- MagicQueue.Mode - Enum in org.deeplearning4j.parallelism
-
Deprecated.
- MagicQueue.Type - Enum in org.deeplearning4j.parallelism
-
Deprecated.
- main(String[]) - Static method in class com.atilika.kuromoji.ipadic.compile.DictionaryCompiler
-
- main(String[]) - Static method in class org.ansj.app.crf.MakeTrainFile
-
- main(String[]) - Static method in class org.ansj.util.MathUtil
-
- main(String[]) - Static method in class org.deeplearning4j.aws.ec2.provision.ClusterSetup
-
- main(String[]) - Static method in class org.deeplearning4j.aws.ec2.provision.DistributedDeepLearningTrainer
-
- main(String[]) - Static method in class org.deeplearning4j.nearestneighbor.server.NearestNeighborsServer
-
- main(String[]) - Static method in class org.deeplearning4j.parallelism.main.ParallelWrapperMain
-
- main(String[]) - Static method in class org.deeplearning4j.perf.listener.SystemInfoTest
-
The main method.
- main(String[]) - Static method in class org.deeplearning4j.text.corpora.sentiwordnet.SWN3
-
- main(String[]) - Static method in class org.deeplearning4j.ui.play.PlayUIServer
-
- makeCategoryReferences() - Method in class com.atilika.kuromoji.compile.UnknownDictionaryCompiler
-
- makeCharacterCategoryMap() - Method in class com.atilika.kuromoji.compile.CharacterDefinitionsCompiler
-
- makeCosts() - Method in class com.atilika.kuromoji.compile.UnknownDictionaryCompiler
-
- makeFeatureArr(List<Element>, int) - Method in class org.ansj.app.crf.Config
-
得到一个位置的所有特征
- makeFeatures() - Method in class com.atilika.kuromoji.compile.UnknownDictionaryCompiler
-
- makeIndex(INDArray) - Method in interface org.deeplearning4j.clustering.lsh.LSH
-
Populates the index with data vectors.
- makeIndex(INDArray) - Method in class org.deeplearning4j.clustering.lsh.RandomProjectionLSH
-
Populates the index.
- makeNewTerm() - Method in class org.ansj.recognition.arrimpl.ForeignPersonRecognition
-
- makeNewTermNum(Term, Term, TermNatures) - Static method in class org.ansj.util.TermUtil
-
将两个term合并为一个全新的term
- makeTable(int, double) - Method in class org.deeplearning4j.models.embeddings.inmemory.InMemoryLookupTable
-
- makeTable(int, double) - Method in class org.deeplearning4j.spark.models.embeddings.word2vec.NegativeHolder
-
- makeToElementList(String, String) - Static method in class org.ansj.app.crf.Config
-
- makeToElementList(String) - Method in class org.ansj.app.crf.Config
-
- MakeTrainFile - Class in org.ansj.app.crf
-
生成crf 或者是 wapiti的训练语聊工具.
- MakeTrainFile() - Constructor for class org.ansj.app.crf.MakeTrainFile
-
- man - Variable in class org.deeplearning4j.datasets.fetchers.MnistDataFetcher
-
- manhattanDistance(double[], double[]) - Static method in class org.deeplearning4j.clustering.util.MathUtils
-
This will calculate the Manhattan distance between two sets of points.
- mapActivation(String, KerasLayerConfiguration) - Static method in class org.deeplearning4j.nn.modelimport.keras.utils.KerasActivationUtils
-
Map Keras to DL4J activation functions.
- mapConstraint(String, KerasLayerConfiguration, Map<String, Object>) - Static method in class org.deeplearning4j.nn.modelimport.keras.utils.KerasConstraintUtils
-
Map Keras to DL4J constraint.
- MapDBStatsStorage - Class in org.deeplearning4j.ui.storage.mapdb
-
- MapDBStatsStorage() - Constructor for class org.deeplearning4j.ui.storage.mapdb.MapDBStatsStorage
-
- MapDBStatsStorage(File) - Constructor for class org.deeplearning4j.ui.storage.mapdb.MapDBStatsStorage
-
- MapDBStatsStorage.Builder - Class in org.deeplearning4j.ui.storage.mapdb
-
- mapFeatures(List<String>) - Method in class com.atilika.kuromoji.buffer.FeatureInfoMap
-
- mapLossFunction(String, KerasLayerConfiguration) - Static method in class org.deeplearning4j.nn.modelimport.keras.utils.KerasLossUtils
-
Map Keras to DL4J loss functions.
- mapper() - Static method in class org.deeplearning4j.models.sequencevectors.sequence.SequenceElement
-
- mapper() - Static method in class org.deeplearning4j.nn.conf.NeuralNetConfiguration
-
Object mapper for serialization of configurations
- MapPerPartitionVoidFunction - Class in org.deeplearning4j.spark.text.functions
-
- MapPerPartitionVoidFunction() - Constructor for class org.deeplearning4j.spark.text.functions.MapPerPartitionVoidFunction
-
- mapperYaml() - Static method in class org.deeplearning4j.nn.conf.NeuralNetConfiguration
-
Object mapper for serialization of configurations
- mapPoolingDimensions(String, KerasLayerConfiguration) - Static method in class org.deeplearning4j.nn.modelimport.keras.layers.pooling.KerasPoolingUtils
-
Map Keras pooling layers to DL4J pooling dimensions.
- mapPoolingType(String, KerasLayerConfiguration) - Static method in class org.deeplearning4j.nn.modelimport.keras.layers.pooling.KerasPoolingUtils
-
Map Keras pooling layers to DL4J pooling types.
- mapRRMDSI(JavaRDD<List<Writable>>, RecordReaderMultiDataSetIterator) - Static method in class org.deeplearning4j.spark.datavec.iterator.IteratorUtils
-
- mapRRMDSI(List<JavaRDD<List<Writable>>>, List<JavaRDD<List<List<Writable>>>>, int[], int[], boolean, RecordReaderMultiDataSetIterator) - Static method in class org.deeplearning4j.spark.datavec.iterator.IteratorUtils
-
Apply to an arbitrary mix of non-sequence and sequence data, in the form of JavaRDD<List<Writable>>
and JavaRDD<List<List<Writable>>>.
Note: this method performs a join by key.
- mapRRMDSIRecords(JavaRDD<DataVecRecords>, RecordReaderMultiDataSetIterator) - Static method in class org.deeplearning4j.spark.datavec.iterator.IteratorUtils
-
- mapRRMDSISeq(JavaRDD<List<List<Writable>>>, RecordReaderMultiDataSetIterator) - Static method in class org.deeplearning4j.spark.datavec.iterator.IteratorUtils
-
- MapToPairFunction - Class in org.deeplearning4j.spark.models.embeddings.word2vec
-
- MapToPairFunction() - Constructor for class org.deeplearning4j.spark.models.embeddings.word2vec.MapToPairFunction
-
- MapTupleToPairFlatMap<T,U> - Class in org.deeplearning4j.spark.impl.common.repartition
-
This is a simple function used to convert a JavaRDD<Tuple2<T,U>> to a JavaPairRDD<T,U> via a
{JavaRDD.mappartitionsToPair()} call.
- MapTupleToPairFlatMap() - Constructor for class org.deeplearning4j.spark.impl.common.repartition.MapTupleToPairFlatMap
-
- mapWeightInitialization(String, KerasLayerConfiguration, Map<String, Object>, int) - Static method in class org.deeplearning4j.nn.modelimport.keras.utils.KerasInitilizationUtils
-
Map Keras to DL4J weight initialization functions.
- margin(LengthUnit, Integer, Integer, Integer, Integer) - Method in class org.deeplearning4j.ui.api.Style.Builder
-
- margin(LengthUnit, Double, Double, Double, Double) - Method in class org.deeplearning4j.ui.api.Style.Builder
-
- marginBottom - Variable in class org.deeplearning4j.ui.api.Style.Builder
-
- marginBottom - Variable in class org.deeplearning4j.ui.api.Style
-
- marginLeft - Variable in class org.deeplearning4j.ui.api.Style.Builder
-
- marginLeft - Variable in class org.deeplearning4j.ui.api.Style
-
- marginRight - Variable in class org.deeplearning4j.ui.api.Style.Builder
-
- marginRight - Variable in class org.deeplearning4j.ui.api.Style
-
- marginTop - Variable in class org.deeplearning4j.ui.api.Style.Builder
-
- marginTop - Variable in class org.deeplearning4j.ui.api.Style
-
- marginUnit - Variable in class org.deeplearning4j.ui.api.Style.Builder
-
- marginUnit - Variable in class org.deeplearning4j.ui.api.Style
-
- markAsLabel(boolean) - Method in class org.deeplearning4j.models.sequencevectors.sequence.SequenceElement
-
This method specifies, whether this element should be treated as label for some sequence/document or not.
- mask - Variable in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
-
- maskArray - Variable in class org.deeplearning4j.nn.layers.AbstractLayer
-
- maskArray - Variable in class org.deeplearning4j.nn.layers.variational.VariationalAutoencoder
-
- maskedPoolingConvolution(PoolingType, INDArray, INDArray, boolean, int) - Static method in class org.deeplearning4j.util.MaskedReductionUtil
-
- maskedPoolingEpsilonCnn(PoolingType, INDArray, INDArray, INDArray, boolean, int) - Static method in class org.deeplearning4j.util.MaskedReductionUtil
-
- maskedPoolingEpsilonTimeSeries(PoolingType, INDArray, INDArray, INDArray, int) - Static method in class org.deeplearning4j.util.MaskedReductionUtil
-
- maskedPoolingTimeSeries(PoolingType, INDArray, INDArray, int) - Static method in class org.deeplearning4j.util.MaskedReductionUtil
-
- MaskedReductionUtil - Class in org.deeplearning4j.util
-
This is a TEMPORARY class for implementing global pooling with masking.
- MaskLayer - Class in org.deeplearning4j.nn.conf.layers.util
-
MaskLayer applies the mask array to the forward pass activations, and backward pass gradients, passing through
this layer.
- MaskLayer() - Constructor for class org.deeplearning4j.nn.conf.layers.util.MaskLayer
-
- MaskLayer - Class in org.deeplearning4j.nn.layers.util
-
MaskLayer applies the mask array to the forward pass activations, and backward pass gradients, passing through
this layer.
- MaskLayer(NeuralNetConfiguration) - Constructor for class org.deeplearning4j.nn.layers.util.MaskLayer
-
- maskShape - Variable in class org.deeplearning4j.nn.conf.graph.ReshapeVertex
-
- MaskState - Enum in org.deeplearning4j.nn.api
-
MaskState: specifies whether a mask should be applied or not.
- maskState - Variable in class org.deeplearning4j.nn.layers.AbstractLayer
-
- MaskZeroLayer - Class in org.deeplearning4j.nn.conf.layers.util
-
- MaskZeroLayer(Layer) - Constructor for class org.deeplearning4j.nn.conf.layers.util.MaskZeroLayer
-
- MaskZeroLayer - Class in org.deeplearning4j.nn.layers.recurrent
-
Masks timesteps with 0 activation.
- MaskZeroLayer(Layer) - Constructor for class org.deeplearning4j.nn.layers.recurrent.MaskZeroLayer
-
- matchesAnyStopWord(List<String>, String) - Static method in class org.deeplearning4j.text.movingwindow.Util
-
- MathUtil - Class in org.ansj.util
-
- MathUtil() - Constructor for class org.ansj.util.MathUtil
-
- MathUtils - Class in org.deeplearning4j.clustering.util
-
This is a math utils class.
- MathUtils() - Constructor for class org.deeplearning4j.clustering.util.MathUtils
-
- MatrixUtil - Class in org.ansj.util
-
- MatrixUtil() - Constructor for class org.ansj.util.MatrixUtil
-
- matthewsCorrelation(int) - Method in class org.deeplearning4j.eval.Evaluation
-
Calculate the binary Mathews correlation coefficient, for the specified class.
MCC = (TP*TN - FP*FN) / sqrt((TP+FP)(TP+FN)(TN+FP)(TN+FN))
- matthewsCorrelation(EvaluationAveraging) - Method in class org.deeplearning4j.eval.Evaluation
-
Calculate the average binary Mathews correlation coefficient, using macro or micro averaging.
MCC = (TP*TN - FP*FN) / sqrt((TP+FP)(TP+FN)(TN+FP)(TN+FN))
Note: This is NOT the same as the multi-class Matthews correlation coefficient
- matthewsCorrelation(int) - Method in class org.deeplearning4j.eval.EvaluationBinary
-
Calculate the Matthews correlation coefficient for the specified output
- matthewsCorrelation(long, long, long, long) - Static method in class org.deeplearning4j.eval.EvaluationUtils
-
Calculate the binary Matthews correlation coefficient from counts
- max(double[]) - Static method in class org.deeplearning4j.clustering.util.MathUtils
-
- max(DataSet, DataSet) - Method in class org.deeplearning4j.spark.ordering.DataSetOrdering
-
- MAX_CODE_LENGTH - Variable in class org.deeplearning4j.models.word2vec.Huffman
-
- MAX_COUNT - Static variable in class org.deeplearning4j.spark.models.embeddings.glove.GlovePerformer
-
- MAX_EXP - Static variable in class org.deeplearning4j.graph.models.embeddings.InMemoryGraphLookupTable
-
- MAX_EXP - Static variable in class org.deeplearning4j.models.embeddings.inmemory.InMemoryLookupTable
-
- MAX_EXP - Static variable in class org.deeplearning4j.models.embeddings.learning.impl.elements.CBOW
-
- MAX_EXP - Static variable in class org.deeplearning4j.models.embeddings.learning.impl.sequence.DM
-
- MAX_QUERY_RETRIES - Static variable in class org.deeplearning4j.spark.time.NTPTimeSource
-
- maxBatchesPerWorker - Variable in class org.deeplearning4j.spark.api.WorkerConfiguration
-
- maxCount(double) - Method in class org.deeplearning4j.models.glove.GloveWeightLookupTable.Builder
-
Deprecated.
- maxCount(double) - Method in class org.deeplearning4j.spark.models.embeddings.glove.GloveParam.Builder
-
- MaxEpochsTerminationCondition - Class in org.deeplearning4j.earlystopping.termination
-
Terminate training if the number of epochs exceeds the maximum number of epochs
- MaxEpochsTerminationCondition(int) - Constructor for class org.deeplearning4j.earlystopping.termination.MaxEpochsTerminationCondition
-
- maxFrom(Model, Element) - Method in class org.ansj.app.crf.pojo.Element
-
- maxIndex(double[]) - Static method in class org.deeplearning4j.clustering.util.MathUtils
-
Returns index of maximum element in a given
array of doubles.
- maxIter - Variable in class org.deeplearning4j.plot.BarnesHutTsne
-
- maxIter - Variable in class org.deeplearning4j.plot.Tsne.Builder
-
- maxIter - Variable in class org.deeplearning4j.plot.Tsne
-
- maxmemory - Variable in class org.deeplearning4j.models.embeddings.learning.impl.elements.GloVe.Builder
-
- maxMemory(int) - Method in class org.deeplearning4j.models.embeddings.learning.impl.elements.GloVe.Builder
-
This method allows you to specify maximum memory available for CoOccurrence map builder.
- maxmemory - Variable in class org.deeplearning4j.models.embeddings.learning.impl.elements.GloVe
-
- maxmemory - Variable in class org.deeplearning4j.models.glove.AbstractCoOccurrences.Builder
-
- maxMemory(int) - Method in class org.deeplearning4j.models.glove.AbstractCoOccurrences.Builder
-
This method allows you to specify maximum memory available for CoOccurrence map builder.
- maxMemory(int) - Method in class org.deeplearning4j.models.glove.Glove.Builder
-
This method allows you to specify maximum memory available for CoOccurrence map builder.
- MaxNormConstraint - Class in org.deeplearning4j.nn.conf.constraint
-
Constrain the maximum L2 norm of the incoming weights for each unit to be less than or equal to the specified value.
- MaxNormConstraint(double, Set<String>, int...) - Constructor for class org.deeplearning4j.nn.conf.constraint.MaxNormConstraint
-
- MaxNormConstraint(double, int...) - Constructor for class org.deeplearning4j.nn.conf.constraint.MaxNormConstraint
-
Apply to weights but not biases by default
- maxNumBatches - Variable in class org.deeplearning4j.datasets.datavec.RecordReaderDataSetIterator.Builder
-
- maxNumBatches(int) - Method in class org.deeplearning4j.datasets.datavec.RecordReaderDataSetIterator.Builder
-
Optional argument, usually not used.
- maxNumBatches - Variable in class org.deeplearning4j.datasets.datavec.RecordReaderDataSetIterator
-
- maxNumLineSearchIterations - Variable in class org.deeplearning4j.nn.conf.NeuralNetConfiguration.Builder
-
- maxNumLineSearchIterations(int) - Method in class org.deeplearning4j.nn.conf.NeuralNetConfiguration.Builder
-
Maximum number of line search iterations.
- maxNumLineSearchIterations - Variable in class org.deeplearning4j.nn.conf.NeuralNetConfiguration
-
- maxNumLineSearchIterations(int) - Method in class org.deeplearning4j.nn.transferlearning.FineTuneConfiguration.Builder
-
- maxNumLineSearchIterations - Variable in class org.deeplearning4j.nn.transferlearning.FineTuneConfiguration
-
- maxOutcomeForRow(int) - Method in class org.deeplearning4j.nn.simple.multiclass.RankClassificationResult
-
Get the max index for the given row
- maxOutcomes() - Method in class org.deeplearning4j.nn.simple.multiclass.RankClassificationResult
-
- MaxPerPartitionAccumulator - Class in org.deeplearning4j.spark.text.accumulators
-
- MaxPerPartitionAccumulator() - Constructor for class org.deeplearning4j.spark.text.accumulators.MaxPerPartitionAccumulator
-
- maxPool3x3(int) - Static method in class org.deeplearning4j.zoo.model.helper.FaceNetHelper
-
- maxPoolNxN(int, int) - Static method in class org.deeplearning4j.zoo.model.helper.FaceNetHelper
-
- MaxScoreIterationTerminationCondition - Class in org.deeplearning4j.earlystopping.termination
-
Iteration termination condition for terminating training if the minibatch score exceeds a certain value.
- MaxScoreIterationTerminationCondition(double) - Constructor for class org.deeplearning4j.earlystopping.termination.MaxScoreIterationTerminationCondition
-
- maxSentenceLength(int) - Method in class org.deeplearning4j.iterator.CnnSentenceDataSetIterator.Builder
-
Maximum sentence/document length.
- MaxTimeIterationTerminationCondition - Class in org.deeplearning4j.earlystopping.termination
-
Terminate training based on max time.
- MaxTimeIterationTerminationCondition(long, TimeUnit) - Constructor for class org.deeplearning4j.earlystopping.termination.MaxTimeIterationTerminationCondition
-
- maxValue() - Method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder.PerParameterStatsDecoder.HistogramsDecoder
-
- maxValue(double) - Method in class org.deeplearning4j.ui.stats.sbe.UpdateEncoder.PerParameterStatsEncoder.HistogramsEncoder
-
- maxValueId() - Static method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder.PerParameterStatsDecoder.HistogramsDecoder
-
- maxValueMaxValue() - Static method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder.PerParameterStatsDecoder.HistogramsDecoder
-
- maxValueMaxValue() - Static method in class org.deeplearning4j.ui.stats.sbe.UpdateEncoder.PerParameterStatsEncoder.HistogramsEncoder
-
- maxValueMetaAttribute(MetaAttribute) - Static method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder.PerParameterStatsDecoder.HistogramsDecoder
-
- maxValueMinValue() - Static method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder.PerParameterStatsDecoder.HistogramsDecoder
-
- maxValueMinValue() - Static method in class org.deeplearning4j.ui.stats.sbe.UpdateEncoder.PerParameterStatsEncoder.HistogramsEncoder
-
- maxValueNullValue() - Static method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder.PerParameterStatsDecoder.HistogramsDecoder
-
- maxValueNullValue() - Static method in class org.deeplearning4j.ui.stats.sbe.UpdateEncoder.PerParameterStatsEncoder.HistogramsEncoder
-
- maxVertexInputs() - Method in class org.deeplearning4j.nn.conf.graph.ElementWiseVertex
-
- maxVertexInputs() - Method in class org.deeplearning4j.nn.conf.graph.FrozenVertex
-
- maxVertexInputs() - Method in class org.deeplearning4j.nn.conf.graph.GraphVertex
-
- maxVertexInputs() - Method in class org.deeplearning4j.nn.conf.graph.L2NormalizeVertex
-
- maxVertexInputs() - Method in class org.deeplearning4j.nn.conf.graph.L2Vertex
-
- maxVertexInputs() - Method in class org.deeplearning4j.nn.conf.graph.LayerVertex
-
- maxVertexInputs() - Method in class org.deeplearning4j.nn.conf.graph.MergeVertex
-
- maxVertexInputs() - Method in class org.deeplearning4j.nn.conf.graph.PoolHelperVertex
-
- maxVertexInputs() - Method in class org.deeplearning4j.nn.conf.graph.PreprocessorVertex
-
- maxVertexInputs() - Method in class org.deeplearning4j.nn.conf.graph.ReshapeVertex
-
- maxVertexInputs() - Method in class org.deeplearning4j.nn.conf.graph.rnn.DuplicateToTimeSeriesVertex
-
- maxVertexInputs() - Method in class org.deeplearning4j.nn.conf.graph.rnn.LastTimeStepVertex
-
- maxVertexInputs() - Method in class org.deeplearning4j.nn.conf.graph.rnn.ReverseTimeSeriesVertex
-
- maxVertexInputs() - Method in class org.deeplearning4j.nn.conf.graph.ScaleVertex
-
- maxVertexInputs() - Method in class org.deeplearning4j.nn.conf.graph.ShiftVertex
-
- maxVertexInputs() - Method in class org.deeplearning4j.nn.conf.graph.StackVertex
-
- maxVertexInputs() - Method in class org.deeplearning4j.nn.conf.graph.SubsetVertex
-
- maxVertexInputs() - Method in class org.deeplearning4j.nn.conf.graph.UnstackVertex
-
- mds - Variable in class org.deeplearning4j.optimize.listeners.EvaluativeListener
-
- mdsIterator - Variable in class org.deeplearning4j.earlystopping.scorecalc.base.BaseScoreCalculator
-
- mdsIterator - Variable in class org.deeplearning4j.optimize.listeners.EvaluativeListener
-
- mean(double[]) - Static method in class org.deeplearning4j.clustering.util.MathUtils
-
Computes the mean for an array of doubles.
- meanAbsoluteError(int) - Method in class org.deeplearning4j.eval.RegressionEvaluation
-
- meanActivations() - Method in class org.deeplearning4j.ui.stats.sbe.UpdateFieldsPresentDecoder
-
- meanActivations(boolean) - Method in class org.deeplearning4j.ui.stats.sbe.UpdateFieldsPresentEncoder
-
- meanGradients() - Method in class org.deeplearning4j.ui.stats.sbe.UpdateFieldsPresentDecoder
-
- meanGradients(boolean) - Method in class org.deeplearning4j.ui.stats.sbe.UpdateFieldsPresentEncoder
-
- meanMagnitudeActivations() - Method in class org.deeplearning4j.ui.stats.sbe.UpdateFieldsPresentDecoder
-
- meanMagnitudeActivations(boolean) - Method in class org.deeplearning4j.ui.stats.sbe.UpdateFieldsPresentEncoder
-
- meanMagnitudeGradients() - Method in class org.deeplearning4j.ui.stats.sbe.UpdateFieldsPresentDecoder
-
- meanMagnitudeGradients(boolean) - Method in class org.deeplearning4j.ui.stats.sbe.UpdateFieldsPresentEncoder
-
- meanMagnitudeParameters() - Method in class org.deeplearning4j.ui.stats.sbe.UpdateFieldsPresentDecoder
-
- meanMagnitudeParameters(boolean) - Method in class org.deeplearning4j.ui.stats.sbe.UpdateFieldsPresentEncoder
-
- meanMagnitudeUpdates() - Method in class org.deeplearning4j.ui.stats.sbe.UpdateFieldsPresentDecoder
-
- meanMagnitudeUpdates(boolean) - Method in class org.deeplearning4j.ui.stats.sbe.UpdateFieldsPresentEncoder
-
- meanParameters() - Method in class org.deeplearning4j.ui.stats.sbe.UpdateFieldsPresentDecoder
-
- meanParameters(boolean) - Method in class org.deeplearning4j.ui.stats.sbe.UpdateFieldsPresentEncoder
-
- meanSquaredError(int) - Method in class org.deeplearning4j.eval.RegressionEvaluation
-
- meanUpdates() - Method in class org.deeplearning4j.ui.stats.sbe.UpdateFieldsPresentDecoder
-
- meanUpdates(boolean) - Method in class org.deeplearning4j.ui.stats.sbe.UpdateFieldsPresentEncoder
-
- memCellActivations - Variable in class org.deeplearning4j.nn.layers.recurrent.FwdPassReturn
-
- memCellState - Variable in class org.deeplearning4j.nn.layers.recurrent.FwdPassReturn
-
- memory_threshold - Variable in class org.deeplearning4j.models.glove.AbstractCoOccurrences
-
- memoryBytes() - Method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder.MemoryUseDecoder
-
- memoryBytes(long) - Method in class org.deeplearning4j.ui.stats.sbe.UpdateEncoder.MemoryUseEncoder
-
- memoryBytesId() - Static method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder.MemoryUseDecoder
-
- memoryBytesMaxValue() - Static method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder.MemoryUseDecoder
-
- memoryBytesMaxValue() - Static method in class org.deeplearning4j.ui.stats.sbe.UpdateEncoder.MemoryUseEncoder
-
- memoryBytesMetaAttribute(MetaAttribute) - Static method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder.MemoryUseDecoder
-
- memoryBytesMinValue() - Static method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder.MemoryUseDecoder
-
- memoryBytesMinValue() - Static method in class org.deeplearning4j.ui.stats.sbe.UpdateEncoder.MemoryUseEncoder
-
- memoryBytesNullValue() - Static method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder.MemoryUseDecoder
-
- memoryBytesNullValue() - Static method in class org.deeplearning4j.ui.stats.sbe.UpdateEncoder.MemoryUseEncoder
-
- memoryParameters(long, int) - Method in class org.deeplearning4j.optimize.solvers.accumulation.EncodedGradientsAccumulator.Builder
-
This method allows to define buffer memory parameters for this GradientsAccumulator
Default values: 100MB initialMemory, 5 queueSize
- MemoryReport - Class in org.deeplearning4j.nn.conf.memory
-
A MemoryReport is designed to represent the estimated memory usage of a model, as a function of:
- Training vs.
- MemoryReport() - Constructor for class org.deeplearning4j.nn.conf.memory.MemoryReport
-
- MemoryType - Enum in org.deeplearning4j.nn.conf.memory
-
Type of memory
- MemoryType - Enum in org.deeplearning4j.ui.stats.sbe
-
- memoryType() - Method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder.MemoryUseDecoder
-
- memoryType(MemoryType) - Method in class org.deeplearning4j.ui.stats.sbe.UpdateEncoder.MemoryUseEncoder
-
- memoryTypeId() - Static method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder.MemoryUseDecoder
-
- memoryTypeMetaAttribute(MetaAttribute) - Static method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder.MemoryUseDecoder
-
- memoryUse() - Method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder
-
- memoryUse() - Method in class org.deeplearning4j.ui.stats.sbe.UpdateFieldsPresentDecoder
-
- memoryUse(boolean) - Method in class org.deeplearning4j.ui.stats.sbe.UpdateFieldsPresentEncoder
-
- memoryUseCount(int) - Method in class org.deeplearning4j.ui.stats.sbe.UpdateEncoder
-
- MemoryUseDecoder() - Constructor for class org.deeplearning4j.ui.stats.sbe.UpdateDecoder.MemoryUseDecoder
-
- memoryUseDecoderId() - Static method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder
-
- MemoryUseEncoder() - Constructor for class org.deeplearning4j.ui.stats.sbe.UpdateEncoder.MemoryUseEncoder
-
- memoryUseId() - Static method in class org.deeplearning4j.ui.stats.sbe.UpdateEncoder
-
- MemoryUseMode - Enum in org.deeplearning4j.nn.conf.memory
-
This simple enumeration defines the memory is used during inference or training.
- merage(Term) - Method in class org.ansj.domain.Term
-
进行term合并
- merageWithBlank(Term) - Method in class org.ansj.domain.Term
-
进行term合并,能合并空白字符
- merge(List<T>) - Method in class org.deeplearning4j.datasets.iterator.file.BaseFileIterator
-
- merge(List<DataSet>) - Method in class org.deeplearning4j.datasets.iterator.file.FileDataSetIterator
-
- merge(List<MultiDataSet>) - Method in class org.deeplearning4j.datasets.iterator.file.FileMultiDataSetIterator
-
- merge(Evaluation) - Method in class org.deeplearning4j.eval.Evaluation
-
Merge the other evaluation object into this one.
- merge(EvaluationBinary) - Method in class org.deeplearning4j.eval.EvaluationBinary
-
- merge(EvaluationCalibration) - Method in class org.deeplearning4j.eval.EvaluationCalibration
-
- merge(T) - Method in interface org.deeplearning4j.eval.IEvaluation
-
- merge(RegressionEvaluation) - Method in class org.deeplearning4j.eval.RegressionEvaluation
-
- merge(ROC) - Method in class org.deeplearning4j.eval.ROC
-
Merge this ROC instance with another.
- merge(ROCBinary) - Method in class org.deeplearning4j.eval.ROCBinary
-
- merge(ROCMultiClass) - Method in class org.deeplearning4j.eval.ROCMultiClass
-
Merge this ROCMultiClass instance with another.
- mergeAndStoreRemainder(List<T>) - Method in class org.deeplearning4j.datasets.iterator.file.BaseFileIterator
-
- mergeCoords(double[], double[]) - Static method in class org.deeplearning4j.clustering.util.MathUtils
-
This will merge the coordinates of the given coordinate system.
- mergeCoords(List<Double>, List<Double>) - Static method in class org.deeplearning4j.clustering.util.MathUtils
-
This will merge the coordinates of the given coordinate system.
- Merger() - Constructor for class org.ansj.splitWord.Analysis.Merger
-
- merger() - Method in class org.ansj.splitWord.Analysis.Merger
-
- MergeVertex - Class in org.deeplearning4j.nn.conf.graph
-
A MergeVertex is used to combine the activations of two or more layers/GraphVertex by means of concatenation/merging.
Exactly how this is done depends on the type of input.
For 2d (feed forward layer) inputs: MergeVertex([numExamples,layerSize1],[numExamples,layerSize2]) -> [numExamples,layerSize1 + layerSize2]
For 3d (time series) inputs: MergeVertex([numExamples,layerSize1,timeSeriesLength],[numExamples,layerSize2,timeSeriesLength])
-> [numExamples,layerSize1 + layerSize2,timeSeriesLength]
For 4d (convolutional) inputs: MergeVertex([numExamples,depth1,width,height],[numExamples,depth2,width,height])
-> [numExamples,depth1 + depth2,width,height]
- MergeVertex() - Constructor for class org.deeplearning4j.nn.conf.graph.MergeVertex
-
- MergeVertex - Class in org.deeplearning4j.nn.graph.vertex.impl
-
A MergeVertex is used to combine the activations of two or more layers/GraphVertex by means of concatenation/merging.
Exactly how this is done depends on the type of input.
For 2d (feed forward layer) inputs: MergeVertex([numExamples,layerSize1],[numExamples,layerSize2]) -> [numExamples,layerSize1 + layerSize2]
For 3d (time series) inputs: MergeVertex([numExamples,layerSize1,timeSeriesLength],[numExamples,layerSize2,timeSeriesLength])
-> [numExamples,layerSize1 + layerSize2,timeSeriesLength]
For 4d (convolutional) inputs: MergeVertex([numExamples,depth1,width,height],[numExamples,depth2,width,height])
-> [numExamples,depth1 + depth2,width,height]
- MergeVertex(ComputationGraph, String, int) - Constructor for class org.deeplearning4j.nn.graph.vertex.impl.MergeVertex
-
- MergeVertex(ComputationGraph, String, int, VertexIndices[], VertexIndices[]) - Constructor for class org.deeplearning4j.nn.graph.vertex.impl.MergeVertex
-
- messageHandler(MessageHandler) - Method in class org.deeplearning4j.optimize.solvers.accumulation.EncodedGradientsAccumulator.Builder
-
This method allows to specify MessageHandler instance
Default value: EncodingHandler
- MessageHandler - Interface in org.deeplearning4j.optimize.solvers.accumulation
-
This interface describes communication primitive for GradientsAccumulator
PLEASE NOTE: All implementations of this interface must be thread-safe.
- messageHandlerClass - Variable in class org.deeplearning4j.spark.parameterserver.conf.SharedTrainingConfiguration
-
- MessageHeaderDecoder - Class in org.deeplearning4j.ui.stats.sbe
-
- MessageHeaderDecoder() - Constructor for class org.deeplearning4j.ui.stats.sbe.MessageHeaderDecoder
-
- MessageHeaderEncoder - Class in org.deeplearning4j.ui.stats.sbe
-
- MessageHeaderEncoder() - Constructor for class org.deeplearning4j.ui.stats.sbe.MessageHeaderEncoder
-
- messages - Variable in class org.deeplearning4j.optimize.solvers.accumulation.EncodedGradientsAccumulator
-
- MetaAttribute - Enum in org.deeplearning4j.ui.stats.sbe
-
- metaData() - Method in interface org.deeplearning4j.zoo.InstantiableModel
-
Deprecated.
- metaData() - Method in class org.deeplearning4j.zoo.model.AlexNet
-
- metaData() - Method in class org.deeplearning4j.zoo.model.Darknet19
-
- metaData() - Method in class org.deeplearning4j.zoo.model.FaceNetNN4Small2
-
- metaData() - Method in class org.deeplearning4j.zoo.model.InceptionResNetV1
-
- metaData() - Method in class org.deeplearning4j.zoo.model.LeNet
-
- metaData() - Method in class org.deeplearning4j.zoo.model.NASNet
-
- metaData() - Method in class org.deeplearning4j.zoo.model.ResNet50
-
- metaData() - Method in class org.deeplearning4j.zoo.model.SimpleCNN
-
- metaData() - Method in class org.deeplearning4j.zoo.model.SqueezeNet
-
- metaData() - Method in class org.deeplearning4j.zoo.model.TextGenerationLSTM
-
- metaData() - Method in class org.deeplearning4j.zoo.model.TinyYOLO
-
- metaData() - Method in class org.deeplearning4j.zoo.model.UNet
-
- metaData() - Method in class org.deeplearning4j.zoo.model.VGG16
-
- metaData() - Method in class org.deeplearning4j.zoo.model.VGG19
-
- metaData() - Method in class org.deeplearning4j.zoo.model.Xception
-
- metaData() - Method in class org.deeplearning4j.zoo.model.YOLO2
-
- metaDataBytes() - Method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder.DataSetMetaDataBytesDecoder
-
- metaDataBytesCount(int) - Method in class org.deeplearning4j.ui.stats.sbe.UpdateEncoder.DataSetMetaDataBytesEncoder
-
- MetaDataBytesDecoder() - Constructor for class org.deeplearning4j.ui.stats.sbe.UpdateDecoder.DataSetMetaDataBytesDecoder.MetaDataBytesDecoder
-
- metaDataBytesDecoderId() - Static method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder.DataSetMetaDataBytesDecoder
-
- MetaDataBytesEncoder() - Constructor for class org.deeplearning4j.ui.stats.sbe.UpdateEncoder.DataSetMetaDataBytesEncoder.MetaDataBytesEncoder
-
- metaDataBytesId() - Static method in class org.deeplearning4j.ui.stats.sbe.UpdateEncoder.DataSetMetaDataBytesEncoder
-
- metric - Variable in class org.deeplearning4j.earlystopping.scorecalc.AutoencoderScoreCalculator
-
- metric - Variable in class org.deeplearning4j.earlystopping.scorecalc.ClassificationScoreCalculator
-
- metric - Variable in class org.deeplearning4j.earlystopping.scorecalc.RegressionScoreCalculator
-
- metric - Variable in class org.deeplearning4j.earlystopping.scorecalc.ROCScoreCalculator
-
- metric - Variable in class org.deeplearning4j.earlystopping.scorecalc.VAEReconErrorScoreCalculator
-
- min(double[]) - Static method in class org.deeplearning4j.clustering.util.MathUtils
-
- min(DataSet, DataSet) - Method in class org.deeplearning4j.spark.ordering.DataSetOrdering
-
- MIN_ALPHA - Static variable in class org.deeplearning4j.spark.models.embeddings.word2vec.Word2VecPerformerVoid
-
Deprecated.
- MIN_ALPHA - Static variable in class org.deeplearning4j.spark.models.embeddings.word2vec.Word2VecVariables
-
Deprecated.
- MIN_UPDATE_FREQUENCY - Static variable in class org.deeplearning4j.spark.time.NTPTimeSource
-
- minDistance(INDArray) - Method in class org.deeplearning4j.clustering.kdtree.HyperRect
-
- minElementFrequency - Variable in class org.deeplearning4j.models.word2vec.wordstore.inmemory.AbstractCache.Builder
-
- minElementFrequency(int) - Method in class org.deeplearning4j.models.word2vec.wordstore.inmemory.AbstractCache.Builder
-
- minGain(double) - Method in class org.deeplearning4j.plot.BarnesHutTsne.Builder
-
- minGain - Variable in class org.deeplearning4j.plot.BarnesHutTsne
-
- minGain - Variable in class org.deeplearning4j.plot.Tsne.Builder
-
- minGain(double) - Method in class org.deeplearning4j.plot.Tsne.Builder
-
- minGain - Variable in class org.deeplearning4j.plot.Tsne
-
- minibatch(boolean) - Method in class org.deeplearning4j.nn.conf.layers.BatchNormalization.Builder
-
If doing minibatch training or not.
- miniBatch - Variable in class org.deeplearning4j.nn.conf.NeuralNetConfiguration.Builder
-
- miniBatch(boolean) - Method in class org.deeplearning4j.nn.conf.NeuralNetConfiguration.Builder
-
Process input as minibatch vs full dataset.
- miniBatch - Variable in class org.deeplearning4j.nn.conf.NeuralNetConfiguration
-
- miniBatch(boolean) - Method in class org.deeplearning4j.nn.transferlearning.FineTuneConfiguration.Builder
-
Whether scores and gradients should be divided by the minibatch size.
Most users should leave this ast he default value of true.
- miniBatch - Variable in class org.deeplearning4j.nn.transferlearning.FineTuneConfiguration
-
- minibatchCount - Variable in class org.deeplearning4j.earlystopping.scorecalc.base.BaseScoreCalculator
-
- miniBatches() - Method in interface org.deeplearning4j.text.invertedindex.InvertedIndex
-
Iterates over mini batches
- miniBatchesJava() - Method in class org.deeplearning4j.spark.datavec.RDDMiniBatches
-
- minibatchesPerSecond() - Method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder.PerformanceDecoder
-
- minibatchesPerSecond(float) - Method in class org.deeplearning4j.ui.stats.sbe.UpdateEncoder.PerformanceEncoder
-
- minibatchesPerSecondId() - Static method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder.PerformanceDecoder
-
- minibatchesPerSecondMaxValue() - Static method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder.PerformanceDecoder
-
- minibatchesPerSecondMaxValue() - Static method in class org.deeplearning4j.ui.stats.sbe.UpdateEncoder.PerformanceEncoder
-
- minibatchesPerSecondMetaAttribute(MetaAttribute) - Static method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder.PerformanceDecoder
-
- minibatchesPerSecondMinValue() - Static method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder.PerformanceDecoder
-
- minibatchesPerSecondMinValue() - Static method in class org.deeplearning4j.ui.stats.sbe.UpdateEncoder.PerformanceEncoder
-
- minibatchesPerSecondNullValue() - Static method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder.PerformanceDecoder
-
- minibatchesPerSecondNullValue() - Static method in class org.deeplearning4j.ui.stats.sbe.UpdateEncoder.PerformanceEncoder
-
- MiniBatchFunction(int) - Constructor for class org.deeplearning4j.spark.datavec.RDDMiniBatches.MiniBatchFunction
-
- minibatchSize(int) - Method in class org.deeplearning4j.iterator.CnnSentenceDataSetIterator.Builder
-
Minibatch size to use for the DataSetIterator
- minimize - Variable in class org.deeplearning4j.nn.conf.NeuralNetConfiguration.Builder
-
- minimize(boolean) - Method in class org.deeplearning4j.nn.conf.NeuralNetConfiguration.Builder
-
Objective function to minimize or maximize cost function
Default set to minimize true.
- minimize - Variable in class org.deeplearning4j.nn.conf.NeuralNetConfiguration
-
- minimize(boolean) - Method in class org.deeplearning4j.nn.transferlearning.FineTuneConfiguration.Builder
-
- minimize - Variable in class org.deeplearning4j.nn.transferlearning.FineTuneConfiguration
-
- minLearningRate - Variable in class org.deeplearning4j.models.embeddings.wordvectors.WordVectorsImpl
-
- minLearningRate(double) - Method in class org.deeplearning4j.models.glove.Glove.Builder
-
- minLearningRate(double) - Method in class org.deeplearning4j.models.node2vec.Node2Vec.Builder
-
Deprecated.
- minLearningRate(double) - Method in class org.deeplearning4j.models.paragraphvectors.ParagraphVectors.Builder
-
This method defines minimal learning rate value for training
- minLearningRate - Variable in class org.deeplearning4j.models.sequencevectors.SequenceVectors.Builder
-
- minLearningRate(double) - Method in class org.deeplearning4j.models.sequencevectors.SequenceVectors.Builder
-
This method defines minimum learning rate after decay being applied.
- minLearningRate(double) - Method in class org.deeplearning4j.models.word2vec.Word2Vec.Builder
-
This method defines minimal learning rate value for training
- minLearningRate - Variable in class org.deeplearning4j.spark.models.embeddings.word2vec.Word2Vec.Builder
-
- minLearningRate(double) - Method in class org.deeplearning4j.spark.models.embeddings.word2vec.Word2Vec.Builder
-
This method specifies bottom threshold for learning rate decay
- MinMaxNormConstraint - Class in org.deeplearning4j.nn.conf.constraint
-
Constrain the minimum AND maximum L2 norm of the incoming weights for each unit to be between the specified values.
- MinMaxNormConstraint(double, double, int...) - Constructor for class org.deeplearning4j.nn.conf.constraint.MinMaxNormConstraint
-
Apply to weights but not biases by default
- MinMaxNormConstraint(double, double, double, int...) - Constructor for class org.deeplearning4j.nn.conf.constraint.MinMaxNormConstraint
-
Apply to weights but not biases by default
- MinMaxNormConstraint(double, double, double, Set<String>, int...) - Constructor for class org.deeplearning4j.nn.conf.constraint.MinMaxNormConstraint
-
- minThreshold - Variable in class org.deeplearning4j.optimize.solvers.accumulation.EncodingHandler
-
- minThreshold - Variable in class org.deeplearning4j.spark.parameterserver.conf.SharedTrainingConfiguration
-
- minThreshold - Variable in class org.deeplearning4j.spark.parameterserver.training.SharedTrainingMaster.Builder
-
- minThreshold - Variable in class org.deeplearning4j.spark.parameterserver.training.SharedTrainingMaster
-
- minUpdatesThreshold(double) - Method in class org.deeplearning4j.spark.parameterserver.training.SharedTrainingMaster.Builder
-
Once update with given threshold become too sparse, threshold will be decreased by thresholdStep, but not below minimum threshold
Default value: 1e-5
- minValue() - Method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder.PerParameterStatsDecoder.HistogramsDecoder
-
- minValue(double) - Method in class org.deeplearning4j.ui.stats.sbe.UpdateEncoder.PerParameterStatsEncoder.HistogramsEncoder
-
- minValueId() - Static method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder.PerParameterStatsDecoder.HistogramsDecoder
-
- minValueMaxValue() - Static method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder.PerParameterStatsDecoder.HistogramsDecoder
-
- minValueMaxValue() - Static method in class org.deeplearning4j.ui.stats.sbe.UpdateEncoder.PerParameterStatsEncoder.HistogramsEncoder
-
- minValueMetaAttribute(MetaAttribute) - Static method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder.PerParameterStatsDecoder.HistogramsDecoder
-
- minValueMinValue() - Static method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder.PerParameterStatsDecoder.HistogramsDecoder
-
- minValueMinValue() - Static method in class org.deeplearning4j.ui.stats.sbe.UpdateEncoder.PerParameterStatsEncoder.HistogramsEncoder
-
- minValueNullValue() - Static method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder.PerParameterStatsDecoder.HistogramsDecoder
-
- minValueNullValue() - Static method in class org.deeplearning4j.ui.stats.sbe.UpdateEncoder.PerParameterStatsEncoder.HistogramsEncoder
-
- minVertexInputs() - Method in class org.deeplearning4j.nn.conf.graph.ElementWiseVertex
-
- minVertexInputs() - Method in class org.deeplearning4j.nn.conf.graph.FrozenVertex
-
- minVertexInputs() - Method in class org.deeplearning4j.nn.conf.graph.GraphVertex
-
- minVertexInputs() - Method in class org.deeplearning4j.nn.conf.graph.L2NormalizeVertex
-
- minVertexInputs() - Method in class org.deeplearning4j.nn.conf.graph.L2Vertex
-
- minVertexInputs() - Method in class org.deeplearning4j.nn.conf.graph.LayerVertex
-
- minVertexInputs() - Method in class org.deeplearning4j.nn.conf.graph.MergeVertex
-
- minVertexInputs() - Method in class org.deeplearning4j.nn.conf.graph.PoolHelperVertex
-
- minVertexInputs() - Method in class org.deeplearning4j.nn.conf.graph.PreprocessorVertex
-
- minVertexInputs() - Method in class org.deeplearning4j.nn.conf.graph.ReshapeVertex
-
- minVertexInputs() - Method in class org.deeplearning4j.nn.conf.graph.rnn.DuplicateToTimeSeriesVertex
-
- minVertexInputs() - Method in class org.deeplearning4j.nn.conf.graph.rnn.LastTimeStepVertex
-
- minVertexInputs() - Method in class org.deeplearning4j.nn.conf.graph.rnn.ReverseTimeSeriesVertex
-
- minVertexInputs() - Method in class org.deeplearning4j.nn.conf.graph.ScaleVertex
-
- minVertexInputs() - Method in class org.deeplearning4j.nn.conf.graph.ShiftVertex
-
- minVertexInputs() - Method in class org.deeplearning4j.nn.conf.graph.StackVertex
-
- minVertexInputs() - Method in class org.deeplearning4j.nn.conf.graph.SubsetVertex
-
- minVertexInputs() - Method in class org.deeplearning4j.nn.conf.graph.UnstackVertex
-
- minWordFrequency - Variable in class org.deeplearning4j.bagofwords.vectorizer.BagOfWordsVectorizer.Builder
-
- minWordFrequency - Variable in class org.deeplearning4j.bagofwords.vectorizer.BaseTextVectorizer
-
- minWordFrequency - Variable in class org.deeplearning4j.bagofwords.vectorizer.Builder
-
Deprecated.
- minWordFrequency - Variable in class org.deeplearning4j.bagofwords.vectorizer.TfidfVectorizer.Builder
-
- minWordFrequency - Variable in class org.deeplearning4j.models.embeddings.wordvectors.WordVectorsImpl
-
- minWordFrequency(int) - Method in class org.deeplearning4j.models.glove.Glove.Builder
-
Sets minimum word frequency during vocabulary mastering.
- minWordFrequency(int) - Method in class org.deeplearning4j.models.node2vec.Node2Vec.Builder
-
Deprecated.
- minWordFrequency(int) - Method in class org.deeplearning4j.models.paragraphvectors.ParagraphVectors.Builder
-
This method defines minimal word frequency in training corpus.
- minWordFrequency - Variable in class org.deeplearning4j.models.sequencevectors.SequenceVectors.Builder
-
- minWordFrequency(int) - Method in class org.deeplearning4j.models.sequencevectors.SequenceVectors.Builder
-
This method defines minimal element frequency for elements found in the training corpus.
- minWordFrequency(int) - Method in class org.deeplearning4j.models.word2vec.Word2Vec.Builder
-
This method defines minimal word frequency in training corpus.
- minWordFrequency(int) - Method in class org.deeplearning4j.models.word2vec.wordstore.VocabularyHolder.Builder
-
- minWordFrequency - Variable in class org.deeplearning4j.spark.models.embeddings.word2vec.Word2Vec.Builder
-
- minWordFrequency(int) - Method in class org.deeplearning4j.spark.models.embeddings.word2vec.Word2Vec.Builder
-
This method specifies minimum word frequency threshold.
- minWordFrequency(int) - Method in class org.deeplearning4j.spark.models.sequencevectors.SparkSequenceVectors.Builder
-
- minWordFrequency(int) - Method in class org.deeplearning4j.spark.models.word2vec.SparkWord2Vec.Builder
-
- minWords(int) - Method in class org.deeplearning4j.bagofwords.vectorizer.Builder
-
Deprecated.
- mkOrderingOps(DataSet) - Method in class org.deeplearning4j.spark.ordering.DataSetOrdering
-
- MLLibUtil - Class in org.deeplearning4j.spark.util
-
Dl4j <----> MLLib
- mnist() - Static method in class org.deeplearning4j.datasets.DataSets
-
- mnist(int) - Static method in class org.deeplearning4j.datasets.DataSets
-
- MNIST_ROOT - Static variable in class org.deeplearning4j.datasets.fetchers.MnistDataFetcher
-
- MnistDataFetcher - Class in org.deeplearning4j.datasets.fetchers
-
Data fetcher for the MNIST dataset
- MnistDataFetcher(boolean) - Constructor for class org.deeplearning4j.datasets.fetchers.MnistDataFetcher
-
Constructor telling whether to binarize the dataset or not
- MnistDataFetcher(boolean, boolean, boolean, long) - Constructor for class org.deeplearning4j.datasets.fetchers.MnistDataFetcher
-
- MnistDataFetcher() - Constructor for class org.deeplearning4j.datasets.fetchers.MnistDataFetcher
-
- MnistDataSetIterator - Class in org.deeplearning4j.datasets.iterator.impl
-
Mnist data applyTransformToDestination iterator.
- MnistDataSetIterator(int, int) - Constructor for class org.deeplearning4j.datasets.iterator.impl.MnistDataSetIterator
-
- MnistDataSetIterator(int, int, boolean) - Constructor for class org.deeplearning4j.datasets.iterator.impl.MnistDataSetIterator
-
Get the specified number of examples for the MNIST training data set.
- MnistDataSetIterator(int, boolean, int) - Constructor for class org.deeplearning4j.datasets.iterator.impl.MnistDataSetIterator
-
Constructor to get the full MNIST data set (either test or train sets) without binarization (i.e., just normalization
into range of 0 to 1), with shuffling based on a random seed.
- MnistDataSetIterator(int, int, boolean, boolean, boolean, long) - Constructor for class org.deeplearning4j.datasets.iterator.impl.MnistDataSetIterator
-
Get the specified number of MNIST examples (test or train set), with optional shuffling and binarization.
- MnistDbFile - Class in org.deeplearning4j.datasets.mnist
-
MNIST database file containing entries that can represent image or label
data.
- MnistDbFile(String, String) - Constructor for class org.deeplearning4j.datasets.mnist.MnistDbFile
-
Creates new instance and reads the header information.
- MnistFetcher - Class in org.deeplearning4j.base
-
- MnistFetcher() - Constructor for class org.deeplearning4j.base.MnistFetcher
-
- MnistImageFile - Class in org.deeplearning4j.datasets.mnist
-
MNIST database image file.
- MnistImageFile(String, String) - Constructor for class org.deeplearning4j.datasets.mnist.MnistImageFile
-
Creates new MNIST database image file ready for reading.
- MnistLabelFile - Class in org.deeplearning4j.datasets.mnist
-
MNIST database label file.
- MnistLabelFile(String, String) - Constructor for class org.deeplearning4j.datasets.mnist.MnistLabelFile
-
Creates new MNIST database label file ready for reading.
- MnistManager - Class in org.deeplearning4j.datasets.mnist
-
Utility class for working with the MNIST database.
- MnistManager(String, String, boolean) - Constructor for class org.deeplearning4j.datasets.mnist.MnistManager
-
Constructs an instance managing the two given data files.
- MnistManager(String, String, int) - Constructor for class org.deeplearning4j.datasets.mnist.MnistManager
-
- MnistManager(String, String) - Constructor for class org.deeplearning4j.datasets.mnist.MnistManager
-
- mode(TokenizerBase.Mode) - Method in class com.atilika.kuromoji.ipadic.Tokenizer.Builder
-
Sets the tokenization mode
- mode - Variable in class com.atilika.kuromoji.TokenizerBase.Builder
-
- mode(Bidirectional.Mode) - Method in class org.deeplearning4j.nn.conf.layers.recurrent.Bidirectional.Builder
-
- mode - Variable in class org.deeplearning4j.parallelism.MagicQueue
-
Deprecated.
- Model - Class in org.ansj.app.crf
-
- Model() - Constructor for class org.ansj.app.crf.Model
-
- model - Variable in class org.deeplearning4j.earlystopping.trainer.BaseEarlyStoppingTrainer
-
- Model - Interface in org.deeplearning4j.nn.api
-
A Model is meant for predicting something from data.
- model - Variable in class org.deeplearning4j.nn.modelexport.solr.ltr.model.ScoringModel
-
- model(Model) - Method in class org.deeplearning4j.optimize.Solver.Builder
-
- model - Variable in class org.deeplearning4j.optimize.solvers.BaseOptimizer
-
- model - Variable in class org.deeplearning4j.parallelism.EarlyStoppingParallelTrainer
-
- model - Variable in class org.deeplearning4j.parallelism.ParallelWrapper.Builder
-
- model - Variable in class org.deeplearning4j.parallelism.ParallelWrapper
-
- modelBuilder - Variable in class org.deeplearning4j.nn.modelimport.keras.KerasModel
-
- modelBuilder() - Method in class org.deeplearning4j.nn.modelimport.keras.KerasModel
-
- modelConfigClassName() - Method in class org.deeplearning4j.ui.stats.sbe.StaticInfoDecoder
-
- modelConfigClassName(String) - Method in class org.deeplearning4j.ui.stats.sbe.StaticInfoEncoder
-
- modelConfigClassNameCharacterEncoding() - Static method in class org.deeplearning4j.ui.stats.sbe.StaticInfoDecoder
-
- modelConfigClassNameCharacterEncoding() - Static method in class org.deeplearning4j.ui.stats.sbe.StaticInfoEncoder
-
- modelConfigClassNameHeaderLength() - Static method in class org.deeplearning4j.ui.stats.sbe.StaticInfoDecoder
-
- modelConfigClassNameHeaderLength() - Static method in class org.deeplearning4j.ui.stats.sbe.StaticInfoEncoder
-
- modelConfigClassNameId() - Static method in class org.deeplearning4j.ui.stats.sbe.StaticInfoDecoder
-
- modelConfigClassNameId() - Static method in class org.deeplearning4j.ui.stats.sbe.StaticInfoEncoder
-
- modelConfigClassNameLength() - Method in class org.deeplearning4j.ui.stats.sbe.StaticInfoDecoder
-
- modelConfigClassNameMetaAttribute(MetaAttribute) - Static method in class org.deeplearning4j.ui.stats.sbe.StaticInfoDecoder
-
- modelConfigClassNameMetaAttribute(MetaAttribute) - Static method in class org.deeplearning4j.ui.stats.sbe.StaticInfoEncoder
-
- modelConfigJson() - Method in class org.deeplearning4j.ui.stats.sbe.StaticInfoDecoder
-
- modelConfigJson(String) - Method in class org.deeplearning4j.ui.stats.sbe.StaticInfoEncoder
-
- modelConfigJsonCharacterEncoding() - Static method in class org.deeplearning4j.ui.stats.sbe.StaticInfoDecoder
-
- modelConfigJsonCharacterEncoding() - Static method in class org.deeplearning4j.ui.stats.sbe.StaticInfoEncoder
-
- modelConfigJsonHeaderLength() - Static method in class org.deeplearning4j.ui.stats.sbe.StaticInfoDecoder
-
- modelConfigJsonHeaderLength() - Static method in class org.deeplearning4j.ui.stats.sbe.StaticInfoEncoder
-
- modelConfigJsonId() - Static method in class org.deeplearning4j.ui.stats.sbe.StaticInfoDecoder
-
- modelConfigJsonId() - Static method in class org.deeplearning4j.ui.stats.sbe.StaticInfoEncoder
-
- modelConfigJsonLength() - Method in class org.deeplearning4j.ui.stats.sbe.StaticInfoDecoder
-
- modelConfigJsonMetaAttribute(MetaAttribute) - Static method in class org.deeplearning4j.ui.stats.sbe.StaticInfoDecoder
-
- modelConfigJsonMetaAttribute(MetaAttribute) - Static method in class org.deeplearning4j.ui.stats.sbe.StaticInfoEncoder
-
- modelExporter - Variable in class org.deeplearning4j.spark.models.sequencevectors.SparkSequenceVectors.Builder
-
- ModelGuesser - Class in org.deeplearning4j.util
-
Guess a model from the given path
- ModelGuesser() - Constructor for class org.deeplearning4j.util.ModelGuesser
-
- ModelGuesserException - Exception in org.deeplearning4j.util
-
- ModelGuesserException(String) - Constructor for exception org.deeplearning4j.util.ModelGuesserException
-
- ModelGuesserException(String, Throwable) - Constructor for exception org.deeplearning4j.util.ModelGuesserException
-
- ModelGuesserException(Throwable) - Constructor for exception org.deeplearning4j.util.ModelGuesserException
-
- modelHdf5Filename(String) - Method in class org.deeplearning4j.nn.modelimport.keras.utils.KerasModelBuilder
-
- modelInfo() - Method in class org.deeplearning4j.ui.stats.sbe.InitFieldsPresentDecoder
-
- modelInfo(boolean) - Method in class org.deeplearning4j.ui.stats.sbe.InitFieldsPresentEncoder
-
- modelJson - Variable in class org.deeplearning4j.nn.modelimport.keras.utils.KerasModelBuilder
-
- modelJson(String) - Method in class org.deeplearning4j.nn.modelimport.keras.utils.KerasModelBuilder
-
- modelJsonFilename(String) - Method in class org.deeplearning4j.nn.modelimport.keras.utils.KerasModelBuilder
-
- modelJsonInputStream(InputStream) - Method in class org.deeplearning4j.nn.modelimport.keras.utils.KerasModelBuilder
-
- ModelMetaData - Class in org.deeplearning4j.zoo
-
- ModelMetaData() - Constructor for class org.deeplearning4j.zoo.ModelMetaData
-
Deprecated.
- modelNumLayers() - Method in class org.deeplearning4j.ui.stats.sbe.StaticInfoDecoder
-
- modelNumLayers(int) - Method in class org.deeplearning4j.ui.stats.sbe.StaticInfoEncoder
-
- modelNumLayersId() - Static method in class org.deeplearning4j.ui.stats.sbe.StaticInfoDecoder
-
- modelNumLayersMaxValue() - Static method in class org.deeplearning4j.ui.stats.sbe.StaticInfoDecoder
-
- modelNumLayersMaxValue() - Static method in class org.deeplearning4j.ui.stats.sbe.StaticInfoEncoder
-
- modelNumLayersMetaAttribute(MetaAttribute) - Static method in class org.deeplearning4j.ui.stats.sbe.StaticInfoDecoder
-
- modelNumLayersMinValue() - Static method in class org.deeplearning4j.ui.stats.sbe.StaticInfoDecoder
-
- modelNumLayersMinValue() - Static method in class org.deeplearning4j.ui.stats.sbe.StaticInfoEncoder
-
- modelNumLayersNullValue() - Static method in class org.deeplearning4j.ui.stats.sbe.StaticInfoDecoder
-
- modelNumLayersNullValue() - Static method in class org.deeplearning4j.ui.stats.sbe.StaticInfoEncoder
-
- modelNumParams() - Method in class org.deeplearning4j.ui.stats.sbe.StaticInfoDecoder
-
- modelNumParams(long) - Method in class org.deeplearning4j.ui.stats.sbe.StaticInfoEncoder
-
- modelNumParamsId() - Static method in class org.deeplearning4j.ui.stats.sbe.StaticInfoDecoder
-
- modelNumParamsMaxValue() - Static method in class org.deeplearning4j.ui.stats.sbe.StaticInfoDecoder
-
- modelNumParamsMaxValue() - Static method in class org.deeplearning4j.ui.stats.sbe.StaticInfoEncoder
-
- modelNumParamsMetaAttribute(MetaAttribute) - Static method in class org.deeplearning4j.ui.stats.sbe.StaticInfoDecoder
-
- modelNumParamsMinValue() - Static method in class org.deeplearning4j.ui.stats.sbe.StaticInfoDecoder
-
- modelNumParamsMinValue() - Static method in class org.deeplearning4j.ui.stats.sbe.StaticInfoEncoder
-
- modelNumParamsNullValue() - Static method in class org.deeplearning4j.ui.stats.sbe.StaticInfoDecoder
-
- modelNumParamsNullValue() - Static method in class org.deeplearning4j.ui.stats.sbe.StaticInfoEncoder
-
- modelParamNames() - Method in class org.deeplearning4j.ui.stats.sbe.StaticInfoDecoder
-
- modelParamNames() - Method in class org.deeplearning4j.ui.stats.sbe.StaticInfoDecoder.ModelParamNamesDecoder
-
- modelParamNames(String) - Method in class org.deeplearning4j.ui.stats.sbe.StaticInfoEncoder.ModelParamNamesEncoder
-
- modelParamNamesCharacterEncoding() - Static method in class org.deeplearning4j.ui.stats.sbe.StaticInfoDecoder.ModelParamNamesDecoder
-
- modelParamNamesCharacterEncoding() - Static method in class org.deeplearning4j.ui.stats.sbe.StaticInfoEncoder.ModelParamNamesEncoder
-
- modelParamNamesCount(int) - Method in class org.deeplearning4j.ui.stats.sbe.StaticInfoEncoder
-
- ModelParamNamesDecoder() - Constructor for class org.deeplearning4j.ui.stats.sbe.StaticInfoDecoder.ModelParamNamesDecoder
-
- modelParamNamesDecoderId() - Static method in class org.deeplearning4j.ui.stats.sbe.StaticInfoDecoder
-
- ModelParamNamesEncoder() - Constructor for class org.deeplearning4j.ui.stats.sbe.StaticInfoEncoder.ModelParamNamesEncoder
-
- modelParamNamesHeaderLength() - Static method in class org.deeplearning4j.ui.stats.sbe.StaticInfoDecoder.ModelParamNamesDecoder
-
- modelParamNamesHeaderLength() - Static method in class org.deeplearning4j.ui.stats.sbe.StaticInfoEncoder.ModelParamNamesEncoder
-
- modelParamNamesId() - Static method in class org.deeplearning4j.ui.stats.sbe.StaticInfoDecoder.ModelParamNamesDecoder
-
- modelParamNamesId() - Static method in class org.deeplearning4j.ui.stats.sbe.StaticInfoEncoder.ModelParamNamesEncoder
-
- modelParamNamesId() - Static method in class org.deeplearning4j.ui.stats.sbe.StaticInfoEncoder
-
- modelParamNamesLength() - Method in class org.deeplearning4j.ui.stats.sbe.StaticInfoDecoder.ModelParamNamesDecoder
-
- modelParamNamesMetaAttribute(MetaAttribute) - Static method in class org.deeplearning4j.ui.stats.sbe.StaticInfoDecoder.ModelParamNamesDecoder
-
- modelParamNamesMetaAttribute(MetaAttribute) - Static method in class org.deeplearning4j.ui.stats.sbe.StaticInfoEncoder.ModelParamNamesEncoder
-
- modelSaver(EarlyStoppingModelSaver<T>) - Method in class org.deeplearning4j.earlystopping.EarlyStoppingConfiguration.Builder
-
How should models be saved? (Default: in memory)
- ModelSavingCallback - Class in org.deeplearning4j.optimize.listeners.callbacks
-
This callback will save model after each EvaluativeListener invocation.
- ModelSavingCallback(String) - Constructor for class org.deeplearning4j.optimize.listeners.callbacks.ModelSavingCallback
-
This constructor will create ModelSavingCallback instance that will save models in current folder
PLEASE NOTE: Make sure you have write access to the current folder
- ModelSavingCallback(File, String) - Constructor for class org.deeplearning4j.optimize.listeners.callbacks.ModelSavingCallback
-
This constructor will create ModelSavingCallback instance that will save models in specified folder
PLEASE NOTE: Make sure you have write access to the target folder
- ModelSerializer - Class in org.deeplearning4j.util
-
Utility class suited to save/restore neural net models
- modelType() - Method in interface org.deeplearning4j.zoo.InstantiableModel
-
- modelType() - Method in class org.deeplearning4j.zoo.model.AlexNet
-
- modelType() - Method in class org.deeplearning4j.zoo.model.Darknet19
-
- modelType() - Method in class org.deeplearning4j.zoo.model.FaceNetNN4Small2
-
- modelType() - Method in class org.deeplearning4j.zoo.model.InceptionResNetV1
-
- modelType() - Method in class org.deeplearning4j.zoo.model.LeNet
-
- modelType() - Method in class org.deeplearning4j.zoo.model.NASNet
-
- modelType() - Method in class org.deeplearning4j.zoo.model.ResNet50
-
- modelType() - Method in class org.deeplearning4j.zoo.model.SimpleCNN
-
- modelType() - Method in class org.deeplearning4j.zoo.model.SqueezeNet
-
- modelType() - Method in class org.deeplearning4j.zoo.model.TextGenerationLSTM
-
- modelType() - Method in class org.deeplearning4j.zoo.model.TinyYOLO
-
- modelType() - Method in class org.deeplearning4j.zoo.model.UNet
-
- modelType() - Method in class org.deeplearning4j.zoo.model.VGG16
-
- modelType() - Method in class org.deeplearning4j.zoo.model.VGG19
-
- modelType() - Method in class org.deeplearning4j.zoo.model.Xception
-
- modelType() - Method in class org.deeplearning4j.zoo.model.YOLO2
-
- modelUri - Variable in class org.deeplearning4j.streaming.routes.DL4jServeRouteBuilder
-
- ModelUtils<T extends SequenceElement> - Interface in org.deeplearning4j.models.embeddings.reader
-
Instances implementing this interface should be responsible for utility access to SequenceVectors model
- modelUtils - Variable in class org.deeplearning4j.models.embeddings.wordvectors.WordVectorsImpl
-
- modelUtils(ModelUtils<VocabWord>) - Method in class org.deeplearning4j.models.glove.Glove.Builder
-
Sets ModelUtils that gonna be used as provider for utility methods: similarity(), wordsNearest(), accuracy(), etc
- modelUtils(ModelUtils<V>) - Method in class org.deeplearning4j.models.node2vec.Node2Vec.Builder
-
Deprecated.
- modelUtils(ModelUtils<VocabWord>) - Method in class org.deeplearning4j.models.paragraphvectors.ParagraphVectors.Builder
-
Sets ModelUtils that gonna be used as provider for utility methods: similarity(), wordsNearest(), accuracy(), etc
- modelUtils - Variable in class org.deeplearning4j.models.sequencevectors.SequenceVectors.Builder
-
- modelUtils(ModelUtils<T>) - Method in class org.deeplearning4j.models.sequencevectors.SequenceVectors.Builder
-
ModelUtils implementation, that will be used to access model.
- modelUtils(ModelUtils<VocabWord>) - Method in class org.deeplearning4j.models.word2vec.Word2Vec.Builder
-
Sets ModelUtils that gonna be used as provider for utility methods: similarity(), wordsNearest(), accuracy(), etc
- modelYaml - Variable in class org.deeplearning4j.nn.modelimport.keras.utils.KerasModelBuilder
-
- modelYaml(String) - Method in class org.deeplearning4j.nn.modelimport.keras.utils.KerasModelBuilder
-
- modelYamlFilename(String) - Method in class org.deeplearning4j.nn.modelimport.keras.utils.KerasModelBuilder
-
- modelYamlInputStream(InputStream) - Method in class org.deeplearning4j.nn.modelimport.keras.utils.KerasModelBuilder
-
- module() - Static method in class org.deeplearning4j.ui.providers.ObjectMapperProvider
-
- momentum - Variable in class org.deeplearning4j.plot.BarnesHutTsne
-
- momentum - Variable in class org.deeplearning4j.plot.Tsne.Builder
-
- momentum - Variable in class org.deeplearning4j.plot.Tsne
-
- movingAverage(INDArray, int) - Static method in class org.deeplearning4j.util.TimeSeriesUtils
-
Calculate a moving average given the length
- MovingWindowBaseDataSetIterator - Class in org.deeplearning4j.datasets.iterator
-
DataSetIterator for moving window (rotating matrices)
- MovingWindowBaseDataSetIterator(int, int, DataSet, int, int) - Constructor for class org.deeplearning4j.datasets.iterator.MovingWindowBaseDataSetIterator
-
- MovingWindowDataSetFetcher - Class in org.deeplearning4j.datasets.iterator.impl
-
Moving window data fetcher.
- MovingWindowDataSetFetcher(DataSet, int, int) - Constructor for class org.deeplearning4j.datasets.iterator.impl.MovingWindowDataSetFetcher
-
- MovingWindowMatrix - Class in org.deeplearning4j.util
-
Moving window on a matrix (usually used for images)
Given a: This is a list of flattened arrays:
1 1 1 1 1 1 2 2
2 2 2 2 ----> 1 1 2 2
3 3 3 3 3 3 4 4
4 4 4 4 3 3 4 4
- MovingWindowMatrix(INDArray, int, int, boolean) - Constructor for class org.deeplearning4j.util.MovingWindowMatrix
-
- MovingWindowMatrix(INDArray, int, int) - Constructor for class org.deeplearning4j.util.MovingWindowMatrix
-
Same as calling new MovingWindowMatrix(toSlice,windowRowSize,windowColumnSize,false)
- MultiBoolean - Class in org.deeplearning4j.datasets.iterator.parallel
-
This is utility class, that allows easy handling of multiple joint boolean states.
- MultiBoolean(int) - Constructor for class org.deeplearning4j.datasets.iterator.parallel.MultiBoolean
-
- MultiBoolean(int, boolean) - Constructor for class org.deeplearning4j.datasets.iterator.parallel.MultiBoolean
-
- MultiBoolean(int, boolean, boolean) - Constructor for class org.deeplearning4j.datasets.iterator.parallel.MultiBoolean
-
- MultiDataSetDeserializationCallback - Class in org.deeplearning4j.spark.parameterserver.callbacks
-
- MultiDataSetDeserializationCallback() - Constructor for class org.deeplearning4j.spark.parameterserver.callbacks.MultiDataSetDeserializationCallback
-
- MultiDataSetExportFunction - Class in org.deeplearning4j.spark.data
-
A function (used in forEachPartition) to save MultiDataSet objects to disk/HDFS.
- MultiDataSetExportFunction(URI) - Constructor for class org.deeplearning4j.spark.data.MultiDataSetExportFunction
-
- MultiDataSetIteratorAdapter - Class in org.deeplearning4j.datasets.iterator.impl
-
Iterator that adapts a DataSetIterator to a MultiDataSetIterator
- MultiDataSetIteratorAdapter(DataSetIterator) - Constructor for class org.deeplearning4j.datasets.iterator.impl.MultiDataSetIteratorAdapter
-
- MultiDataSetIteratorSplitter - Class in org.deeplearning4j.datasets.iterator
-
This iterator virtually splits given MultiDataSetIterator into Train and Test parts.
- MultiDataSetIteratorSplitter(MultiDataSetIterator, long, double) - Constructor for class org.deeplearning4j.datasets.iterator.MultiDataSetIteratorSplitter
-
- MultiDataSetProvider - Interface in org.deeplearning4j.spark.data
-
A provider for an MultiDataSet
rdd.
- MultiDataSetProviderFactory - Interface in org.deeplearning4j.parallelism.main
-
Creates an MultiDataSetIterator
- MultiDataSetWrapperIterator - Class in org.deeplearning4j.datasets.iterator
-
This class is simple wrapper that takes single-input MultiDataSets and converts them to DataSets on the fly
PLEASE NOTE: This only works if number of features/labels/masks is 1
- MultiDataSetWrapperIterator(MultiDataSetIterator) - Constructor for class org.deeplearning4j.datasets.iterator.MultiDataSetWrapperIterator
-
- MultiLayerConfiguration - Class in org.deeplearning4j.nn.conf
-
Configuration for a multi layer network
- MultiLayerConfiguration() - Constructor for class org.deeplearning4j.nn.conf.MultiLayerConfiguration
-
- MultiLayerConfiguration.Builder - Class in org.deeplearning4j.nn.conf
-
- MultiLayerConfigurationDeserializer - Class in org.deeplearning4j.nn.conf.serde
-
- MultiLayerConfigurationDeserializer(JsonDeserializer<?>) - Constructor for class org.deeplearning4j.nn.conf.serde.MultiLayerConfigurationDeserializer
-
- MultiLayerNetwork - Class in org.deeplearning4j.nn.multilayer
-
MultiLayerNetwork is a neural network with multiple layers in a stack, and usually an output layer.
- MultiLayerNetwork(MultiLayerConfiguration) - Constructor for class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
-
- MultiLayerNetwork(String, INDArray) - Constructor for class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
-
Initialize the network based on the configuration
- MultiLayerNetwork(MultiLayerConfiguration, INDArray) - Constructor for class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
-
Initialize the network based on the configuraiton
- MultiLayerUpdater - Class in org.deeplearning4j.nn.updater
-
MultiLayerUpdater: Gradient updater for MultiLayerNetworks.
- MultiLayerUpdater(MultiLayerNetwork) - Constructor for class org.deeplearning4j.nn.updater.MultiLayerUpdater
-
- MultiLayerUpdater(MultiLayerNetwork, INDArray) - Constructor for class org.deeplearning4j.nn.updater.MultiLayerUpdater
-
- multiPartUpload(File, String) - Method in class org.deeplearning4j.aws.s3.uploader.S3Uploader
-
Multi part upload for big files
- MultiPdsIterator - Class in org.deeplearning4j.spark.parameterserver.iterators
-
- MultiPdsIterator(Iterator<PortableDataStream>, PortableDataStreamMDSCallback) - Constructor for class org.deeplearning4j.spark.parameterserver.iterators.MultiPdsIterator
-
- MultipleEpochsIterator - Class in org.deeplearning4j.datasets.iterator
-
- MultipleEpochsIterator(int, DataSetIterator) - Constructor for class org.deeplearning4j.datasets.iterator.MultipleEpochsIterator
-
Deprecated.
- MultipleEpochsIterator(int, DataSetIterator, int) - Constructor for class org.deeplearning4j.datasets.iterator.MultipleEpochsIterator
-
Deprecated.
- MultipleEpochsIterator(DataSetIterator, int, long) - Constructor for class org.deeplearning4j.datasets.iterator.MultipleEpochsIterator
-
Deprecated.
- MultipleEpochsIterator(DataSetIterator, long) - Constructor for class org.deeplearning4j.datasets.iterator.MultipleEpochsIterator
-
Deprecated.
- MultipleEpochsIterator(int, DataSet) - Constructor for class org.deeplearning4j.datasets.iterator.MultipleEpochsIterator
-
Deprecated.
- MultiThreadUtils - Class in org.deeplearning4j.clustering.util
-
- MutipleEpochsSentenceIterator - Class in org.deeplearning4j.text.sentenceiterator
-
This SentenceIterator implemenation wraps existing sentence iterator, and resets it numEpochs times
This class is usable for tests purposes mostly.
- MutipleEpochsSentenceIterator(SentenceIterator, int) - Constructor for class org.deeplearning4j.text.sentenceiterator.MutipleEpochsSentenceIterator
-
- MyStaticValue - Class in org.ansj.util
-
这个类储存一些公用变量.
- MyStaticValue() - Constructor for class org.ansj.util.MyStaticValue
-
- n(double) - Method in class org.deeplearning4j.nn.conf.layers.LocalResponseNormalization.Builder
-
Number of adjacent kernel maps to use when doing LRN.
- n - Variable in class org.deeplearning4j.nn.conf.layers.LocalResponseNormalization
-
- N_GRAMS - Static variable in class org.deeplearning4j.spark.models.embeddings.word2vec.Word2VecVariables
-
Deprecated.
- name - Variable in class org.ansj.app.crf.pojo.Element
-
- name(String) - Method in class org.deeplearning4j.nn.conf.layers.Layer.Builder
-
Layer name assigns layer string name.
- name(String) - Method in class org.deeplearning4j.nn.conf.layers.SpaceToBatchLayer.Builder
-
- name(String) - Method in class org.deeplearning4j.nn.conf.layers.SpaceToDepthLayer.Builder
-
- name() - Method in class org.deeplearning4j.nn.layers.ocnn.OCNNOutputLayer.OCNNLossFunction
-
- NAME_SPACE - Static variable in class org.deeplearning4j.spark.models.embeddings.glove.GlovePerformer
-
- NAME_SPACE - Static variable in class org.deeplearning4j.spark.models.embeddings.word2vec.Word2VecPerformerVoid
-
Deprecated.
- NAME_SPACE - Static variable in class org.deeplearning4j.spark.models.embeddings.word2vec.Word2VecVariables
-
Deprecated.
- nameAmbiguity(Term[], Forest...) - Static method in class org.ansj.util.NameFix
-
人名消歧,比如.邓颖超生前->邓颖 超生 前 fix to 丁颖超 生 前! 规则的方式增加如果两个人名之间连接是- ， ·，•则连接
- NameFix - Class in org.ansj.util
-
- NameFix() - Constructor for class org.ansj.util.NameFix
-
- nameLayer(String, String, int) - Static method in class org.deeplearning4j.zoo.model.helper.InceptionResNetHelper
-
- nameProvider(SystemPolling.NameProvider) - Method in class org.deeplearning4j.perf.listener.SystemPolling.Builder
-
The name provider for this
SystemPolling
the default value for this is a simple UUID
- nameStr() - Method in class org.ansj.app.crf.pojo.Element
-
获得可见的名称
- NAN_REPLACEMENT_VALUE - Static variable in class org.deeplearning4j.ui.module.train.TrainModule
-
- NASNet - Class in org.deeplearning4j.zoo.model
-
U-Net
Implementation of NASNet-A in Deeplearning4j.
- NASNetHelper - Class in org.deeplearning4j.zoo.model.helper
-
- NASNetHelper() - Constructor for class org.deeplearning4j.zoo.model.helper.NASNetHelper
-
- natrue() - Method in class org.ansj.domain.Term
-
获得这个词的词性.词性计算后才可生效
- nature - Variable in class org.ansj.app.crf.pojo.Element
-
- Nature - Class in org.ansj.domain
-
这里面封装了一些基本的词性.
- Nature(String, int, int, int) - Constructor for class org.ansj.domain.Nature
-
- Nature(String) - Constructor for class org.ansj.domain.Nature
-
- nature - Variable in class org.ansj.domain.TermNature
-
- nature - Variable in class org.ansj.domain.TermNatures
-
默认词性
- natureIndex - Variable in class org.ansj.domain.Nature
-
- NatureLibrary - Class in org.ansj.library
-
这里封装了词性和词性之间的关系.以及词性的索引.这是个好东西.
- NatureLibrary() - Constructor for class org.ansj.library.NatureLibrary
-
- NatureRecognition - Class in org.ansj.recognition.impl
-
词性标注工具类
- NatureRecognition() - Constructor for class org.ansj.recognition.impl.NatureRecognition
-
- NatureRecognition(Forest...) - Constructor for class org.ansj.recognition.impl.NatureRecognition
-
- NatureRecognition.NatureTerm - Class in org.ansj.recognition.impl
-
关于这个term的词性
- natureStr - Variable in class org.ansj.domain.Nature
-
- NatureTerm(TermNature) - Constructor for class org.ansj.recognition.impl.NatureRecognition.NatureTerm
-
- nBins() - Method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder.PerParameterStatsDecoder.HistogramsDecoder
-
- nBins(int) - Method in class org.deeplearning4j.ui.stats.sbe.UpdateEncoder.PerParameterStatsEncoder.HistogramsEncoder
-
- nBinsId() - Static method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder.PerParameterStatsDecoder.HistogramsDecoder
-
- nBinsMaxValue() - Static method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder.PerParameterStatsDecoder.HistogramsDecoder
-
- nBinsMaxValue() - Static method in class org.deeplearning4j.ui.stats.sbe.UpdateEncoder.PerParameterStatsEncoder.HistogramsEncoder
-
- nBinsMetaAttribute(MetaAttribute) - Static method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder.PerParameterStatsDecoder.HistogramsDecoder
-
- nBinsMinValue() - Static method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder.PerParameterStatsDecoder.HistogramsDecoder
-
- nBinsMinValue() - Static method in class org.deeplearning4j.ui.stats.sbe.UpdateEncoder.PerParameterStatsEncoder.HistogramsEncoder
-
- nBinsNullValue() - Static method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder.PerParameterStatsDecoder.HistogramsDecoder
-
- nBinsNullValue() - Static method in class org.deeplearning4j.ui.stats.sbe.UpdateEncoder.PerParameterStatsEncoder.HistogramsEncoder
-
- NDARRAY_TYPE - Static variable in class org.deeplearning4j.streaming.kafka.NDArrayPublisher
-
- NDARRAY_TYPE_HEADER - Static variable in class org.deeplearning4j.streaming.kafka.NDArrayKafkaClient
-
- NDArrayConsumer - Class in org.deeplearning4j.streaming.kafka
-
NDArray consumer for receiving
ndarrays off of kafka
- NDArrayConsumer() - Constructor for class org.deeplearning4j.streaming.kafka.NDArrayConsumer
-
- NDArrayKafkaClient - Class in org.deeplearning4j.streaming.kafka
-
Created by agibsonccc on 7/31/16.
- NDArrayKafkaClient() - Constructor for class org.deeplearning4j.streaming.kafka.NDArrayKafkaClient
-
- NDArrayPublisher - Class in org.deeplearning4j.streaming.kafka
-
Send an ndarray to a kafka topic
- NDArrayPublisher() - Constructor for class org.deeplearning4j.streaming.kafka.NDArrayPublisher
-
- NDArrayPubSubRoute - Class in org.deeplearning4j.streaming.kafka
-
Created by agibsonccc on 7/31/16.
- NDArrayPubSubRoute() - Constructor for class org.deeplearning4j.streaming.kafka.NDArrayPubSubRoute
-
- NDArrayRecordToNDArray - Class in org.deeplearning4j.streaming.conversion.ndarray
-
Assumes all records in the given batch are
of type @link{NDArrayWritable}
It extracts the underlying arrays and returns a
concatenated array.
- NDArrayRecordToNDArray() - Constructor for class org.deeplearning4j.streaming.conversion.ndarray.NDArrayRecordToNDArray
-
- NDArrayType - Enum in org.deeplearning4j.streaming.kafka
-
Used for headers to distinguish
the type of ndarray message
being sent.
- nearestCluster(Point) - Method in class org.deeplearning4j.clustering.cluster.ClusterSet
-
- nearestLabels(LabelledDocument, int) - Method in class org.deeplearning4j.models.paragraphvectors.ParagraphVectors
-
This method returns top N labels nearest to specified document
- nearestLabels(String, int) - Method in class org.deeplearning4j.models.paragraphvectors.ParagraphVectors
-
This method returns top N labels nearest to specified text
- nearestLabels(Collection<VocabWord>, int) - Method in class org.deeplearning4j.models.paragraphvectors.ParagraphVectors
-
This method returns top N labels nearest to specified set of vocab words
- nearestLabels(INDArray, int) - Method in class org.deeplearning4j.models.paragraphvectors.ParagraphVectors
-
This method returns top N labels nearest to specified features vector
- NearestNeighbor - Class in org.deeplearning4j.nearestneighbor.server
-
Created by agibsonccc on 4/27/17.
- NearestNeighbor() - Constructor for class org.deeplearning4j.nearestneighbor.server.NearestNeighbor
-
- NearestNeighborRequest - Class in org.deeplearning4j.nearestneighbor.model
-
Created by agibsonccc on 4/26/17.
- NearestNeighborRequest() - Constructor for class org.deeplearning4j.nearestneighbor.model.NearestNeighborRequest
-
- NearestNeighborsClient - Class in org.deeplearning4j.nearestneighbor.client
-
Client for the nearest neighbors server.
- NearestNeighborsClient(String) - Constructor for class org.deeplearning4j.nearestneighbor.client.NearestNeighborsClient
-
- NearestNeighborsQuery - Class in org.deeplearning4j.ui.nearestneighbors.word2vec
-
- NearestNeighborsQuery(String, int) - Constructor for class org.deeplearning4j.ui.nearestneighbors.word2vec.NearestNeighborsQuery
-
- NearestNeighborsQuery() - Constructor for class org.deeplearning4j.ui.nearestneighbors.word2vec.NearestNeighborsQuery
-
- NearestNeighborsResult - Class in org.deeplearning4j.nearestneighbor.model
-
Created by agibsonccc on 4/26/17.
- NearestNeighborsResult(int, double) - Constructor for class org.deeplearning4j.nearestneighbor.model.NearestNeighborsResult
-
- NearestNeighborsResults - Class in org.deeplearning4j.nearestneighbor.model
-
Created by agibsonccc on 4/27/17.
- NearestNeighborsResults() - Constructor for class org.deeplearning4j.nearestneighbor.model.NearestNeighborsResults
-
- NearestNeighborsServer - Class in org.deeplearning4j.nearestneighbor.server
-
A rest server for using an
VPTree based on loading an ndarray containing
the data points for the path
The input values are an
CSVRecord
which (based on the input schema) will automatically
have their values transformed.
- NearestNeighborsServer() - Constructor for class org.deeplearning4j.nearestneighbor.server.NearestNeighborsServer
-
- NearestVertexWalker<V extends SequenceElement> - Class in org.deeplearning4j.models.sequencevectors.graph.walkers.impl
-
This walker represents connections of a given node + their neighborhoods up to certain depth.
- NearestVertexWalker() - Constructor for class org.deeplearning4j.models.sequencevectors.graph.walkers.impl.NearestVertexWalker
-
- NearestVertexWalker.Builder<V extends SequenceElement> - Class in org.deeplearning4j.models.sequencevectors.graph.walkers.impl
-
- NearestVertexWalker.VertexComparator<V extends SequenceElement,E extends Number> - Class in org.deeplearning4j.models.sequencevectors.graph.walkers.impl
-
- needsLabels() - Method in interface org.deeplearning4j.nn.api.layers.IOutputLayer
-
Returns true if labels are required
for this output layer
- needsLabels() - Method in class org.deeplearning4j.nn.layers.BaseOutputLayer
-
- needsLabels() - Method in class org.deeplearning4j.nn.layers.convolution.CnnLossLayer
-
- needsLabels() - Method in class org.deeplearning4j.nn.layers.LossLayer
-
- needsLabels() - Method in class org.deeplearning4j.nn.layers.objdetect.Yolo2OutputLayer
-
- needsLabels() - Method in class org.deeplearning4j.nn.layers.ocnn.OCNNOutputLayer
-
- needsLabels() - Method in class org.deeplearning4j.nn.layers.recurrent.RnnLossLayer
-
- negative() - Method in class org.deeplearning4j.eval.Evaluation
-
Total negatives true negatives + false negatives
- negative - Variable in class org.deeplearning4j.models.embeddings.inmemory.InMemoryLookupTable.Builder
-
- negative(double) - Method in class org.deeplearning4j.models.embeddings.inmemory.InMemoryLookupTable.Builder
-
- negative - Variable in class org.deeplearning4j.models.embeddings.inmemory.InMemoryLookupTable
-
- negative - Variable in class org.deeplearning4j.models.embeddings.learning.impl.elements.CBOW
-
- negative - Variable in class org.deeplearning4j.models.embeddings.learning.impl.elements.SkipGram
-
- negative - Variable in class org.deeplearning4j.models.embeddings.learning.impl.sequence.DBOW
-
- negative - Variable in class org.deeplearning4j.models.embeddings.learning.impl.sequence.DM
-
- negative - Variable in class org.deeplearning4j.models.embeddings.wordvectors.WordVectorsImpl
-
- negative(double) - Method in class org.deeplearning4j.models.glove.GloveWeightLookupTable.Builder
-
Deprecated.
- negative - Variable in class org.deeplearning4j.models.sequencevectors.SequenceVectors.Builder
-
- negative(double) - Method in class org.deeplearning4j.spark.models.embeddings.glove.GloveParam.Builder
-
- negative - Variable in class org.deeplearning4j.spark.models.embeddings.word2vec.Word2Vec.Builder
-
- negative(int) - Method in class org.deeplearning4j.spark.models.embeddings.word2vec.Word2Vec.Builder
-
Specifies negative sampling
- negative(double) - Method in class org.deeplearning4j.spark.models.embeddings.word2vec.Word2VecParam.Builder
-
Deprecated.
- NEGATIVE - Static variable in class org.deeplearning4j.spark.models.embeddings.word2vec.Word2VecPerformerVoid
-
Deprecated.
- NEGATIVE - Static variable in class org.deeplearning4j.spark.models.embeddings.word2vec.Word2VecVariables
-
Deprecated.
- NegativeDefaultStepFunction - Class in org.deeplearning4j.nn.conf.stepfunctions
-
Inverse step function
- NegativeDefaultStepFunction() - Constructor for class org.deeplearning4j.nn.conf.stepfunctions.NegativeDefaultStepFunction
-
- NegativeDefaultStepFunction - Class in org.deeplearning4j.optimize.stepfunctions
-
Inverse step function
- NegativeDefaultStepFunction() - Constructor for class org.deeplearning4j.optimize.stepfunctions.NegativeDefaultStepFunction
-
- NegativeGradientStepFunction - Class in org.deeplearning4j.nn.conf.stepfunctions
-
Subtract the line
- NegativeGradientStepFunction() - Constructor for class org.deeplearning4j.nn.conf.stepfunctions.NegativeGradientStepFunction
-
- NegativeGradientStepFunction - Class in org.deeplearning4j.optimize.stepfunctions
-
Subtract the line
- NegativeGradientStepFunction() - Constructor for class org.deeplearning4j.optimize.stepfunctions.NegativeGradientStepFunction
-
- NegativeHolder - Class in org.deeplearning4j.spark.models.embeddings.word2vec
-
Simple singleton holder class for w2v negative sampling, to avoid syn1Neg creation for each spark node
- negativeSample(double) - Method in class org.deeplearning4j.models.glove.Glove.Builder
-
Deprecated.
- negativeSample(double) - Method in class org.deeplearning4j.models.node2vec.Node2Vec.Builder
-
Deprecated.
- negativeSample(double) - Method in class org.deeplearning4j.models.paragraphvectors.ParagraphVectors.Builder
-
This method defines whether negative sampling should be used or not
PLEASE NOTE: If you're going to use negative sampling, you might want to disable HierarchicSoftmax, which is enabled by default
Default value: 0
- negativeSample(double) - Method in class org.deeplearning4j.models.sequencevectors.SequenceVectors.Builder
-
This method defines negative sampling value for skip-gram algorithm.
- negativeSample(double) - Method in class org.deeplearning4j.models.word2vec.Word2Vec.Builder
-
This method defines whether negative sampling should be used or not
PLEASE NOTE: If you're going to use negative sampling, you might want to disable HierarchicSoftmax, which is enabled by default
Default value: 0
- negativeSampling(long) - Method in class org.deeplearning4j.spark.models.sequencevectors.SparkSequenceVectors.Builder
-
- negativeSampling(long) - Method in class org.deeplearning4j.spark.models.word2vec.SparkWord2Vec.Builder
-
- negLogProbability(INDArray, INDArray, boolean) - Method in class org.deeplearning4j.nn.conf.layers.variational.BernoulliReconstructionDistribution
-
- negLogProbability(INDArray, INDArray, boolean) - Method in class org.deeplearning4j.nn.conf.layers.variational.CompositeReconstructionDistribution
-
- negLogProbability(INDArray, INDArray, boolean) - Method in class org.deeplearning4j.nn.conf.layers.variational.ExponentialReconstructionDistribution
-
- negLogProbability(INDArray, INDArray, boolean) - Method in class org.deeplearning4j.nn.conf.layers.variational.GaussianReconstructionDistribution
-
- negLogProbability(INDArray, INDArray, boolean) - Method in class org.deeplearning4j.nn.conf.layers.variational.LossFunctionWrapper
-
- negLogProbability(INDArray, INDArray, boolean) - Method in interface org.deeplearning4j.nn.conf.layers.variational.ReconstructionDistribution
-
Calculate the negative log probability (summed or averaged over each example in the minibatch)
- NetBroadcastTuple - Class in org.deeplearning4j.spark.api.worker
-
A simple class for storing configurations, parameters and updaters in one class (so they can be broadcast together)
- NetBroadcastTuple(MultiLayerConfiguration, INDArray, INDArray) - Constructor for class org.deeplearning4j.spark.api.worker.NetBroadcastTuple
-
- NetBroadcastTuple(ComputationGraphConfiguration, INDArray, INDArray) - Constructor for class org.deeplearning4j.spark.api.worker.NetBroadcastTuple
-
- NetBroadcastTuple(MultiLayerConfiguration, ComputationGraphConfiguration, INDArray, INDArray) - Constructor for class org.deeplearning4j.spark.api.worker.NetBroadcastTuple
-
- NetBroadcastTuple(MultiLayerConfiguration, ComputationGraphConfiguration, INDArray, INDArray, AtomicInteger) - Constructor for class org.deeplearning4j.spark.api.worker.NetBroadcastTuple
-
- network - Variable in class org.deeplearning4j.nn.updater.BaseMultiLayerUpdater
-
- networkInputs - Variable in class org.deeplearning4j.nn.conf.ComputationGraphConfiguration.GraphBuilder
-
- networkInputs - Variable in class org.deeplearning4j.nn.conf.ComputationGraphConfiguration
-
List of inputs to the network, by name
- networkInputTypes - Variable in class org.deeplearning4j.nn.conf.ComputationGraphConfiguration.GraphBuilder
-
- NetworkMemoryReport - Class in org.deeplearning4j.nn.conf.memory
-
Network memory reports is a class that is used to store/represent the memory requirements of a
MultiLayerNetwork or
ComputationGraph,
composed of multiple layers and/or vertices.
- NetworkMemoryReport(Map<String, MemoryReport>, Class<?>, String, InputType...) - Constructor for class org.deeplearning4j.nn.conf.memory.NetworkMemoryReport
-
- networkOutputs - Variable in class org.deeplearning4j.nn.conf.ComputationGraphConfiguration.GraphBuilder
-
- networkOutputs - Variable in class org.deeplearning4j.nn.conf.ComputationGraphConfiguration
-
List of network outputs, by name
- NetworkUtils - Class in org.deeplearning4j.util
-
- NeuralNetConfiguration - Class in org.deeplearning4j.nn.conf
-
A Serializable configuration
for neural nets that covers per layer parameters
- NeuralNetConfiguration() - Constructor for class org.deeplearning4j.nn.conf.NeuralNetConfiguration
-
- NeuralNetConfiguration.Builder - Class in org.deeplearning4j.nn.conf
-
NeuralNetConfiguration builder, used as a starting point for creating a MultiLayerConfiguration or
ComputationGraphConfiguration.
Note that values set here on the layer will be applied to all relevant layers - unless the value is overridden
on a layer's configuration
- NeuralNetConfiguration.ListBuilder - Class in org.deeplearning4j.nn.conf
-
Fluent interface for building a list of configurations
- NeuralNetConfiguration.ListBuilder.InputTypeBuilder - Class in org.deeplearning4j.nn.conf
-
Helper class for setting input types
- NeuralNetwork - Interface in org.deeplearning4j.nn.api
-
- newEpoch - Variable in class org.deeplearning4j.datasets.iterator.MultipleEpochsIterator
-
Deprecated.
- newEval() - Method in class org.deeplearning4j.earlystopping.scorecalc.base.BaseIEvaluationScoreCalculator
-
- newEval() - Method in class org.deeplearning4j.earlystopping.scorecalc.ClassificationScoreCalculator
-
- newEval() - Method in class org.deeplearning4j.earlystopping.scorecalc.RegressionScoreCalculator
-
- newEval() - Method in class org.deeplearning4j.earlystopping.scorecalc.ROCScoreCalculator
-
- newExecutorService() - Static method in class org.deeplearning4j.clustering.util.MultiThreadUtils
-
- newInstance(ResourceResolver) - Static method in class com.atilika.kuromoji.dict.CharacterDefinitions
-
- newInstance(ResourceResolver) - Static method in class com.atilika.kuromoji.dict.ConnectionCosts
-
- newInstance(ResourceResolver) - Static method in class com.atilika.kuromoji.dict.TokenInfoDictionary
-
- newInstance(ResourceResolver, CharacterDefinitions, int) - Static method in class com.atilika.kuromoji.dict.UnknownDictionary
-
- newInstance(ResourceResolver) - Static method in class com.atilika.kuromoji.trie.DoubleArrayTrie
-
- newShape - Variable in class org.deeplearning4j.nn.conf.graph.ReshapeVertex
-
- NewWord - Class in org.ansj.domain
-
新词发现,实体名
- NewWord(String, Nature, double) - Constructor for class org.ansj.domain.NewWord
-
- NewWord(String, Nature) - Constructor for class org.ansj.domain.NewWord
-
- NewWordRecognition - Class in org.ansj.recognition.arrimpl
-
新词识别
- NewWordRecognition(LearnTool) - Constructor for class org.ansj.recognition.arrimpl.NewWordRecognition
-
- next() - Method in class org.ansj.domain.Term
-
- next() - Method in class org.ansj.splitWord.Analysis
-
while 循环调用.直到返回为null则分词结束
- next() - Method in class org.deeplearning4j.aws.s3.reader.BucketIterator
-
- next(int) - Method in class org.deeplearning4j.datasets.datavec.RecordReaderDataSetIterator
-
- next() - Method in class org.deeplearning4j.datasets.datavec.RecordReaderDataSetIterator
-
- next() - Method in class org.deeplearning4j.datasets.datavec.RecordReaderMultiDataSetIterator
-
- next(int) - Method in class org.deeplearning4j.datasets.datavec.RecordReaderMultiDataSetIterator
-
- next() - Method in class org.deeplearning4j.datasets.datavec.SequenceRecordReaderDataSetIterator
-
- next(int) - Method in class org.deeplearning4j.datasets.datavec.SequenceRecordReaderDataSetIterator
-
- next() - Method in class org.deeplearning4j.datasets.fetchers.MnistDataFetcher
-
- next(int) - Method in class org.deeplearning4j.datasets.iterator.AbstractDataSetIterator
-
Like the standard next method but allows a
customizable number of examples returned
- next() - Method in class org.deeplearning4j.datasets.iterator.AbstractDataSetIterator
-
Returns the next element in the iteration.
- next(int) - Method in class org.deeplearning4j.datasets.iterator.AsyncDataSetIterator
-
Like the standard next method but allows a
customizable number of examples returned
- next() - Method in class org.deeplearning4j.datasets.iterator.AsyncDataSetIterator
-
Returns the next element in the iteration.
- next(int) - Method in class org.deeplearning4j.datasets.iterator.AsyncMultiDataSetIterator
-
Like the standard next method but allows a
customizable number of examples returned
- next() - Method in class org.deeplearning4j.datasets.iterator.AsyncMultiDataSetIterator
-
Returns the next element in the iteration.
- next(int) - Method in class org.deeplearning4j.datasets.iterator.AsyncShieldDataSetIterator
-
Like the standard next method but allows a
customizable number of examples returned
- next() - Method in class org.deeplearning4j.datasets.iterator.AsyncShieldDataSetIterator
-
Returns the next element in the iteration.
- next(int) - Method in class org.deeplearning4j.datasets.iterator.AsyncShieldMultiDataSetIterator
-
Fetch the next 'num' examples.
- next() - Method in class org.deeplearning4j.datasets.iterator.AsyncShieldMultiDataSetIterator
-
Returns the next element in the iteration.
- next() - Method in class org.deeplearning4j.datasets.iterator.BaseDatasetIterator
-
- next(int) - Method in class org.deeplearning4j.datasets.iterator.BaseDatasetIterator
-
- next() - Method in interface org.deeplearning4j.datasets.iterator.DataSetFetcher
-
Deprecated.
Returns the next data applyTransformToDestination
- next(int) - Method in class org.deeplearning4j.datasets.iterator.EarlyTerminationDataSetIterator
-
- next() - Method in class org.deeplearning4j.datasets.iterator.EarlyTerminationDataSetIterator
-
- next(int) - Method in class org.deeplearning4j.datasets.iterator.EarlyTerminationMultiDataSetIterator
-
- next() - Method in class org.deeplearning4j.datasets.iterator.EarlyTerminationMultiDataSetIterator
-
- next(int) - Method in class org.deeplearning4j.datasets.iterator.ExistingDataSetIterator
-
- next() - Method in class org.deeplearning4j.datasets.iterator.ExistingDataSetIterator
-
- next() - Method in class org.deeplearning4j.datasets.iterator.file.BaseFileIterator
-
- next(int) - Method in class org.deeplearning4j.datasets.iterator.file.FileDataSetIterator
-
- next(int) - Method in class org.deeplearning4j.datasets.iterator.file.FileMultiDataSetIterator
-
- next(int) - Method in class org.deeplearning4j.datasets.iterator.FileSplitDataSetIterator
-
- next() - Method in class org.deeplearning4j.datasets.iterator.FileSplitDataSetIterator
-
- next(int) - Method in class org.deeplearning4j.datasets.iterator.impl.BenchmarkDataSetIterator
-
- next() - Method in class org.deeplearning4j.datasets.iterator.impl.BenchmarkDataSetIterator
-
Returns the next element in the iteration.
- next(int) - Method in class org.deeplearning4j.datasets.iterator.impl.BenchmarkMultiDataSetIterator
-
- next() - Method in class org.deeplearning4j.datasets.iterator.impl.BenchmarkMultiDataSetIterator
-
Returns the next element in the iteration.
- next(int) - Method in class org.deeplearning4j.datasets.iterator.impl.CifarDataSetIterator
-
- next() - Method in class org.deeplearning4j.datasets.iterator.impl.IrisDataSetIterator
-
- next() - Method in class org.deeplearning4j.datasets.iterator.impl.ListDataSetIterator
-
- next(int) - Method in class org.deeplearning4j.datasets.iterator.impl.ListDataSetIterator
-
- next(int) - Method in class org.deeplearning4j.datasets.iterator.impl.MultiDataSetIteratorAdapter
-
- next() - Method in class org.deeplearning4j.datasets.iterator.impl.MultiDataSetIteratorAdapter
-
- next(int) - Method in class org.deeplearning4j.datasets.iterator.impl.SingletonMultiDataSetIterator
-
- next() - Method in class org.deeplearning4j.datasets.iterator.impl.SingletonMultiDataSetIterator
-
- next() - Method in class org.deeplearning4j.datasets.iterator.IteratorDataSetIterator
-
- next(int) - Method in class org.deeplearning4j.datasets.iterator.IteratorDataSetIterator
-
- next() - Method in class org.deeplearning4j.datasets.iterator.IteratorMultiDataSetIterator
-
- next(int) - Method in class org.deeplearning4j.datasets.iterator.IteratorMultiDataSetIterator
-
- next(int) - Method in class org.deeplearning4j.datasets.iterator.MultiDataSetWrapperIterator
-
- next() - Method in class org.deeplearning4j.datasets.iterator.MultiDataSetWrapperIterator
-
- next(int) - Method in class org.deeplearning4j.datasets.iterator.MultipleEpochsIterator
-
Deprecated.
Like the standard next method but allows a
customizable number of examples returned
- next() - Method in class org.deeplearning4j.datasets.iterator.MultipleEpochsIterator
-
Deprecated.
- next() - Method in class org.deeplearning4j.datasets.iterator.parallel.BaseParallelDataSetIterator
-
- next(int) - Method in class org.deeplearning4j.datasets.iterator.parallel.BaseParallelDataSetIterator
-
- next(int) - Method in class org.deeplearning4j.datasets.iterator.ReconstructionDataSetIterator
-
Like the standard next method but allows a
customizable number of examples returned
- next() - Method in class org.deeplearning4j.datasets.iterator.ReconstructionDataSetIterator
-
Returns the next element in the iteration.
- next() - Method in class org.deeplearning4j.datasets.iterator.SamplingDataSetIterator
-
- next(int) - Method in class org.deeplearning4j.datasets.iterator.SamplingDataSetIterator
-
- next(int) - Method in class org.deeplearning4j.datasets.iterator.WorkspacesShieldDataSetIterator
-
- next() - Method in class org.deeplearning4j.datasets.iterator.WorkspacesShieldDataSetIterator
-
- next() - Method in class org.deeplearning4j.datasets.mnist.MnistDbFile
-
Move to the next entry.
- next() - Method in class org.deeplearning4j.datasets.test.TestDataSetIterator
-
- next(int) - Method in class org.deeplearning4j.datasets.test.TestDataSetIterator
-
- next() - Method in class org.deeplearning4j.graph.graph.VertexSequence
-
- next() - Method in interface org.deeplearning4j.graph.iterator.GraphWalkIterator
-
Get the next vertex sequence.
- next() - Method in class org.deeplearning4j.graph.iterator.RandomWalkIterator
-
- next() - Method in class org.deeplearning4j.graph.iterator.WeightedRandomWalkIterator
-
- next() - Method in class org.deeplearning4j.iterator.CnnSentenceDataSetIterator
-
- next(int) - Method in class org.deeplearning4j.iterator.CnnSentenceDataSetIterator
-
- next() - Method in class org.deeplearning4j.models.embeddings.inmemory.InMemoryLookupTable.WeightIterator
-
- next() - Method in class org.deeplearning4j.models.embeddings.loader.WordVectorSerializer.BinaryReader
-
- next() - Method in class org.deeplearning4j.models.embeddings.loader.WordVectorSerializer.CSVReader
-
- next() - Method in interface org.deeplearning4j.models.embeddings.loader.WordVectorSerializer.Reader
-
- next() - Method in interface org.deeplearning4j.models.sequencevectors.graph.walkers.GraphWalker
-
This method returns next walk sequence from this graph
- next() - Method in class org.deeplearning4j.models.sequencevectors.graph.walkers.impl.NearestVertexWalker
-
- next() - Method in class org.deeplearning4j.models.sequencevectors.graph.walkers.impl.PopularityWalker
-
This method returns next walk sequence from this graph
- next() - Method in class org.deeplearning4j.models.sequencevectors.graph.walkers.impl.RandomWalker
-
This method returns next walk sequence from this graph
- next() - Method in class org.deeplearning4j.models.sequencevectors.graph.walkers.impl.WeightedWalker
-
This method returns next walk sequence from this graph
- next() - Method in class org.deeplearning4j.models.sequencevectors.transformers.impl.iterables.BasicTransformerIterator
-
- next() - Method in class org.deeplearning4j.models.sequencevectors.transformers.impl.iterables.ParallelTransformerIterator
-
- next() - Method in class org.deeplearning4j.models.word2vec.iterator.Word2VecDataFetcher
-
- next(int) - Method in class org.deeplearning4j.models.word2vec.iterator.Word2VecDataSetIterator
-
Like the standard next method but allows a
customizable number of examples returned
- next() - Method in class org.deeplearning4j.models.word2vec.iterator.Word2VecDataSetIterator
-
Returns the next element in the iteration.
- next() - Method in class org.deeplearning4j.parallelism.AsyncIterator
-
- next(int) - Method in class org.deeplearning4j.spark.datavec.iterator.SparkSourceDummyReader
-
- next() - Method in class org.deeplearning4j.spark.datavec.iterator.SparkSourceDummyReader
-
- next(int) - Method in class org.deeplearning4j.spark.iterator.BaseDataSetIterator
-
- next() - Method in class org.deeplearning4j.spark.iterator.PathSparkDataSetIterator
-
- next(int) - Method in class org.deeplearning4j.spark.iterator.PathSparkMultiDataSetIterator
-
- next() - Method in class org.deeplearning4j.spark.iterator.PathSparkMultiDataSetIterator
-
- next() - Method in class org.deeplearning4j.spark.iterator.PortableDataStreamDataSetIterator
-
- next(int) - Method in class org.deeplearning4j.spark.iterator.PortableDataStreamMultiDataSetIterator
-
- next() - Method in class org.deeplearning4j.spark.iterator.PortableDataStreamMultiDataSetIterator
-
- next() - Method in class org.deeplearning4j.spark.parameterserver.iterators.MultiPdsIterator
-
- next() - Method in class org.deeplearning4j.spark.parameterserver.iterators.PdsIterator
-
- next() - Method in class org.deeplearning4j.spark.parameterserver.iterators.VirtualDataSetIterator
-
- next(int) - Method in class org.deeplearning4j.spark.parameterserver.iterators.VirtualDataSetIterator
-
- next() - Method in class org.deeplearning4j.spark.parameterserver.iterators.VirtualIterator
-
- next(int) - Method in class org.deeplearning4j.spark.parameterserver.iterators.VirtualMultiDataSetIterator
-
- next() - Method in class org.deeplearning4j.spark.parameterserver.iterators.VirtualMultiDataSetIterator
-
- next() - Method in class org.deeplearning4j.text.corpora.treeparser.TreeIterator
-
Returns the next element in the iteration.
- next() - Method in class org.deeplearning4j.text.documentiterator.AsyncLabelAwareIterator
-
- next() - Method in class org.deeplearning4j.text.documentiterator.BasicLabelAwareIterator
-
- next() - Method in class org.deeplearning4j.text.documentiterator.FileLabelAwareIterator
-
- next() - Method in class org.deeplearning4j.text.documentiterator.FilenamesLabelAwareIterator
-
- next() - Method in class org.deeplearning4j.text.documentiterator.interoperability.DocumentIteratorConverter
-
- next() - Method in class org.deeplearning4j.text.documentiterator.SimpleLabelAwareIterator
-
- next() - Method in class org.deeplearning4j.text.sentenceiterator.interoperability.SentenceIteratorConverter
-
- next() - Method in class org.deeplearning4j.ui.stats.sbe.StaticInfoDecoder.HwDeviceInfoGroupDecoder
-
- next() - Method in class org.deeplearning4j.ui.stats.sbe.StaticInfoDecoder.ModelParamNamesDecoder
-
- next() - Method in class org.deeplearning4j.ui.stats.sbe.StaticInfoDecoder.SwEnvironmentInfoDecoder
-
- next() - Method in class org.deeplearning4j.ui.stats.sbe.StaticInfoEncoder.HwDeviceInfoGroupEncoder
-
- next() - Method in class org.deeplearning4j.ui.stats.sbe.StaticInfoEncoder.ModelParamNamesEncoder
-
- next() - Method in class org.deeplearning4j.ui.stats.sbe.StaticInfoEncoder.SwEnvironmentInfoEncoder
-
- next() - Method in class org.deeplearning4j.ui.stats.sbe.StorageMetaDataDecoder.ExtraMetaDataBytesDecoder
-
- next() - Method in class org.deeplearning4j.ui.stats.sbe.StorageMetaDataEncoder.ExtraMetaDataBytesEncoder
-
- next() - Method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder.DataSetMetaDataBytesDecoder.MetaDataBytesDecoder
-
- next() - Method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder.DataSetMetaDataBytesDecoder
-
- next() - Method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder.GcStatsDecoder
-
- next() - Method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder.LayerNamesDecoder
-
- next() - Method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder.MemoryUseDecoder
-
- next() - Method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder.ParamNamesDecoder
-
- next() - Method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder.PerformanceDecoder
-
- next() - Method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder.PerParameterStatsDecoder.HistogramsDecoder.HistogramCountsDecoder
-
- next() - Method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder.PerParameterStatsDecoder.HistogramsDecoder
-
- next() - Method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder.PerParameterStatsDecoder
-
- next() - Method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder.PerParameterStatsDecoder.SummaryStatDecoder
-
- next() - Method in class org.deeplearning4j.ui.stats.sbe.UpdateEncoder.DataSetMetaDataBytesEncoder.MetaDataBytesEncoder
-
- next() - Method in class org.deeplearning4j.ui.stats.sbe.UpdateEncoder.DataSetMetaDataBytesEncoder
-
- next() - Method in class org.deeplearning4j.ui.stats.sbe.UpdateEncoder.GcStatsEncoder
-
- next() - Method in class org.deeplearning4j.ui.stats.sbe.UpdateEncoder.LayerNamesEncoder
-
- next() - Method in class org.deeplearning4j.ui.stats.sbe.UpdateEncoder.MemoryUseEncoder
-
- next() - Method in class org.deeplearning4j.ui.stats.sbe.UpdateEncoder.ParamNamesEncoder
-
- next() - Method in class org.deeplearning4j.ui.stats.sbe.UpdateEncoder.PerformanceEncoder
-
- next() - Method in class org.deeplearning4j.ui.stats.sbe.UpdateEncoder.PerParameterStatsEncoder.HistogramsEncoder.HistogramCountsEncoder
-
- next() - Method in class org.deeplearning4j.ui.stats.sbe.UpdateEncoder.PerParameterStatsEncoder.HistogramsEncoder
-
- next() - Method in class org.deeplearning4j.ui.stats.sbe.UpdateEncoder.PerParameterStatsEncoder
-
- next() - Method in class org.deeplearning4j.ui.stats.sbe.UpdateEncoder.PerParameterStatsEncoder.SummaryStatEncoder
-
- nextBoolean() - Static method in class org.deeplearning4j.models.embeddings.learning.impl.elements.RandomUtils
-
Returns the next pseudorandom, uniformly distributed boolean value
from the Math.random() sequence.
- nextBoolean(Random) - Static method in class org.deeplearning4j.models.embeddings.learning.impl.elements.RandomUtils
-
Returns the next pseudorandom, uniformly distributed boolean value
from the given random sequence.
- nextBucket() - Method in class org.deeplearning4j.aws.s3.reader.BaseS3DataSetIterator
-
- nextBucket - Variable in class org.deeplearning4j.parallelism.MagicQueue
-
Deprecated.
- nextDocument() - Method in class org.deeplearning4j.text.documentiterator.AsyncLabelAwareIterator
-
- nextDocument() - Method in class org.deeplearning4j.text.documentiterator.BasicLabelAwareIterator
-
This method returns next LabelledDocument
- nextDocument() - Method in interface org.deeplearning4j.text.documentiterator.DocumentIterator
-
Get the next document
- nextDocument() - Method in class org.deeplearning4j.text.documentiterator.FileDocumentIterator
-
- nextDocument() - Method in class org.deeplearning4j.text.documentiterator.FileLabelAwareIterator
-
- nextDocument() - Method in class org.deeplearning4j.text.documentiterator.FilenamesLabelAwareIterator
-
- nextDocument() - Method in class org.deeplearning4j.text.documentiterator.interoperability.DocumentIteratorConverter
-
- nextDocument() - Method in interface org.deeplearning4j.text.documentiterator.LabelAwareIterator
-
- nextDocument() - Method in class org.deeplearning4j.text.documentiterator.SimpleLabelAwareIterator
-
This method returns next LabelledDocument from underlying iterator
- nextDocument() - Method in class org.deeplearning4j.text.sentenceiterator.interoperability.SentenceIteratorConverter
-
- nextDouble() - Static method in class org.deeplearning4j.models.embeddings.learning.impl.elements.RandomUtils
-
Returns the next pseudorandom, uniformly distributed float value
between 0.0 and 1.0 from the Math.random()
sequence.
- nextDouble(Random) - Static method in class org.deeplearning4j.models.embeddings.learning.impl.elements.RandomUtils
-
Returns the next pseudorandom, uniformly distributed float value
between 0.0 and 1.0 from the given Random
sequence.
- nextElement - Variable in class org.deeplearning4j.datasets.iterator.AsyncDataSetIterator
-
- nextElement - Variable in class org.deeplearning4j.datasets.iterator.AsyncMultiDataSetIterator
-
- nextElement - Variable in class org.deeplearning4j.parallelism.AsyncIterator
-
- nextFloat() - Static method in class org.deeplearning4j.models.embeddings.learning.impl.elements.RandomUtils
-
Returns the next pseudorandom, uniformly distributed float value
between 0.0 and 1.0 from the Math.random()
sequence.
- nextFloat(Random) - Static method in class org.deeplearning4j.models.embeddings.learning.impl.elements.RandomUtils
-
Returns the next pseudorandom, uniformly distributed float value
between 0.0 and 1.0 from the given Random
sequence.
- nextFor() - Method in class org.deeplearning4j.datasets.iterator.parallel.BaseParallelDataSetIterator
-
- nextFor(int) - Method in class org.deeplearning4j.datasets.iterator.parallel.BaseParallelDataSetIterator
-
- nextFor(int) - Method in class org.deeplearning4j.datasets.iterator.parallel.FileSplitParallelDataSetIterator
-
- nextFor(int) - Method in class org.deeplearning4j.datasets.iterator.parallel.JointParallelDataSetIterator
-
- nextFor(int) - Method in class org.deeplearning4j.spark.parameterserver.iterators.VirtualMultiDataSetIterator
-
- nextFor() - Method in class org.deeplearning4j.spark.parameterserver.iterators.VirtualMultiDataSetIterator
-
- nextImage() - Method in class org.deeplearning4j.datasets.mnist.MnistImageFile
-
Move the cursor to the next image.
- nextInt() - Static method in class org.deeplearning4j.models.embeddings.learning.impl.elements.RandomUtils
-
Returns the next pseudorandom, uniformly distributed int value
from the Math.random() sequence.
- nextInt(Random) - Static method in class org.deeplearning4j.models.embeddings.learning.impl.elements.RandomUtils
-
Returns the next pseudorandom, uniformly distributed int value
from the given random sequence.
- nextInt(int) - Static method in class org.deeplearning4j.models.embeddings.learning.impl.elements.RandomUtils
-
Returns a pseudorandom, uniformly distributed int value
between 0 (inclusive) and the specified value
(exclusive), from the Math.random() sequence.
- nextInt(Random, int) - Static method in class org.deeplearning4j.models.embeddings.learning.impl.elements.RandomUtils
-
Returns a pseudorandom, uniformly distributed int value
between 0 (inclusive) and the specified value
(exclusive), from the given Random sequence.
- nextLabel() - Method in class org.deeplearning4j.text.documentiterator.LabelsSource
-
Returns next label.
- nextLabel() - Method in interface org.deeplearning4j.text.labels.LabelsProvider
-
- nextList(ObjectListing) - Method in class org.deeplearning4j.aws.s3.reader.S3Downloader
-
Iterator style one list at a time
- nextLong() - Static method in class org.deeplearning4j.models.embeddings.learning.impl.elements.RandomUtils
-
Returns the next pseudorandom, uniformly distributed long value
from the Math.random() sequence.
- nextLong(Random) - Static method in class org.deeplearning4j.models.embeddings.learning.impl.elements.RandomUtils
-
Returns the next pseudorandom, uniformly distributed long value
from the given Random sequence.
- nextMultiDataSet(Map<String, List<List<Writable>>>, Map<String, List<INDArray>>, Map<String, List<List<List<Writable>>>>, List<RecordMetaDataComposableMap>) - Method in class org.deeplearning4j.datasets.datavec.RecordReaderMultiDataSetIterator
-
- nextName() - Method in interface org.deeplearning4j.perf.listener.SystemPolling.NameProvider
-
- nextObject() - Method in class org.deeplearning4j.aws.s3.reader.BaseS3DataSetIterator
-
- nextObject() - Method in class org.deeplearning4j.models.glove.count.ASCIICoOccurrenceReader
-
Returns next CoOccurrenceWeight object
PLEASE NOTE: This method can return null value.
- nextObject() - Method in class org.deeplearning4j.models.glove.count.BinaryCoOccurrenceReader
-
- nextObject() - Method in interface org.deeplearning4j.models.glove.count.CoOccurenceReader
-
- nextPowOf2(long) - Static method in class org.deeplearning4j.clustering.util.MathUtils
-
See: http://stackoverflow.com/questions/466204/rounding-off-to-nearest-power-of-2
- nextRandom - Variable in class org.deeplearning4j.spark.models.sequencevectors.learning.elements.BaseSparkLearningAlgorithm
-
- nextRecord() - Method in class org.deeplearning4j.spark.datavec.iterator.SparkSourceDummyReader
-
- nextSentence() - Method in interface org.deeplearning4j.iterator.LabeledSentenceProvider
-
- nextSentence() - Method in class org.deeplearning4j.iterator.provider.CollectionLabeledSentenceProvider
-
- nextSentence() - Method in class org.deeplearning4j.iterator.provider.FileLabeledSentenceProvider
-
- nextSentence() - Method in class org.deeplearning4j.iterator.provider.LabelAwareConverter
-
- nextSentence() - Method in class org.deeplearning4j.models.sequencevectors.SequenceVectors.AsyncSequencer
-
- nextSentence() - Method in class org.deeplearning4j.text.sentenceiterator.AggregatingSentenceIterator
-
- nextSentence() - Method in class org.deeplearning4j.text.sentenceiterator.BasicLineIterator
-
- nextSentence() - Method in class org.deeplearning4j.text.sentenceiterator.BasicResultSetIterator
-
- nextSentence() - Method in class org.deeplearning4j.text.sentenceiterator.CollectionSentenceIterator
-
- nextSentence() - Method in class org.deeplearning4j.text.sentenceiterator.FileSentenceIterator
-
- nextSentence() - Method in class org.deeplearning4j.text.sentenceiterator.LineSentenceIterator
-
- nextSentence() - Method in class org.deeplearning4j.text.sentenceiterator.MutipleEpochsSentenceIterator
-
- nextSentence() - Method in class org.deeplearning4j.text.sentenceiterator.PrefetchingSentenceIterator
-
Deprecated.
- nextSentence() - Method in interface org.deeplearning4j.text.sentenceiterator.SentenceIterator
-
Gets the next sentence or null
if there's nothing left (Do yourself a favor and
check hasNext() )
- nextSentence() - Method in class org.deeplearning4j.text.sentenceiterator.StreamLineIterator
-
- nextSentence() - Method in class org.deeplearning4j.text.sentenceiterator.SynchronizedSentenceIterator
-
- nextSentence() - Method in class org.deeplearning4j.text.sentenceiterator.UimaResultSetIterator
-
- nextSentence() - Method in class org.deeplearning4j.text.sentenceiterator.UimaSentenceIterator
-
- nextSequence() - Method in interface org.deeplearning4j.models.sequencevectors.interfaces.SequenceIterator
-
- nextSequence() - Method in class org.deeplearning4j.models.sequencevectors.iterators.AbstractSequenceIterator
-
Returns next sequence out of iterator
- nextSequence() - Method in class org.deeplearning4j.models.sequencevectors.iterators.FilteredSequenceIterator
-
Returns filtered sequence, that contains sequence elements from vocabulary only.
- nextSequence() - Method in class org.deeplearning4j.models.sequencevectors.iterators.SynchronizedSequenceIterator
-
Returns next sequence from data source
- nextSequence() - Method in class org.deeplearning4j.spark.datavec.iterator.SparkSourceDummySeqReader
-
- nextToken() - Method in class org.deeplearning4j.text.tokenization.tokenizer.ChineseTokenizer
-
- nextToken() - Method in class org.deeplearning4j.text.tokenization.tokenizer.DefaultStreamTokenizer
-
This method returns next token from prebuffered list of tokens or underlying InputStream
- nextToken() - Method in class org.deeplearning4j.text.tokenization.tokenizer.DefaultTokenizer
-
- nextToken() - Method in class org.deeplearning4j.text.tokenization.tokenizer.JapaneseTokenizer
-
- nextToken() - Method in class org.deeplearning4j.text.tokenization.tokenizer.KoreanTokenizer
-
- nextToken() - Method in class org.deeplearning4j.text.tokenization.tokenizer.NGramTokenizer
-
- nextToken() - Method in class org.deeplearning4j.text.tokenization.tokenizer.PosUimaTokenizer
-
- nextToken() - Method in interface org.deeplearning4j.text.tokenization.tokenizer.Tokenizer
-
The next token (word usually) in the string
- nextToken() - Method in class org.deeplearning4j.text.tokenization.tokenizer.UimaTokenizer
-
- nextWord - Variable in class org.deeplearning4j.models.embeddings.loader.WordVectorSerializer.BinaryReader
-
- NgramLibrary - Class in org.ansj.library
-
两个词之间的关联
- NgramLibrary() - Constructor for class org.ansj.library.NgramLibrary
-
- nGrams - Variable in class org.deeplearning4j.spark.models.embeddings.word2vec.Word2Vec.Builder
-
- NGramTokenizer - Class in org.deeplearning4j.text.tokenization.tokenizer
-
- NGramTokenizer(Tokenizer, Integer, Integer) - Constructor for class org.deeplearning4j.text.tokenization.tokenizer.NGramTokenizer
-
- NGramTokenizerFactory - Class in org.deeplearning4j.text.tokenization.tokenizerfactory
-
- NGramTokenizerFactory(TokenizerFactory, Integer, Integer) - Constructor for class org.deeplearning4j.text.tokenization.tokenizerfactory.NGramTokenizerFactory
-
- nIn(int) - Method in class org.deeplearning4j.nn.conf.layers.CnnLossLayer.Builder
-
- nIn - Variable in class org.deeplearning4j.nn.conf.layers.FeedForwardLayer.Builder
-
- nIn(int) - Method in class org.deeplearning4j.nn.conf.layers.FeedForwardLayer.Builder
-
Number of inputs for the layer (usually the size of the last layer).
- nIn - Variable in class org.deeplearning4j.nn.conf.layers.FeedForwardLayer
-
- nIn(int) - Method in class org.deeplearning4j.nn.conf.layers.LossLayer.Builder
-
- nIn(int) - Method in class org.deeplearning4j.nn.conf.layers.RnnLossLayer.Builder
-
- NlpAnalysis - Class in org.ansj.splitWord.analysis
-
自然语言分词,具有未登录词发现功能。建议在自然语言理解中用。搜索中不要用
- NlpAnalysis() - Constructor for class org.ansj.splitWord.analysis.NlpAnalysis
-
- NlpAnalysis(Reader) - Constructor for class org.ansj.splitWord.analysis.NlpAnalysis
-
- nms(List<DetectedObject>, double) - Static method in class org.deeplearning4j.nn.layers.objdetect.YoloUtils
-
Performs non-maximum suppression (NMS) on objects, using their IOU with threshold to match pairs.
- nn(INDArray) - Method in class org.deeplearning4j.clustering.kdtree.KDTree
-
Query for nearest neighbor.
- NO_PARAMS_MARKER - Static variable in class org.deeplearning4j.util.ModelSerializer
-
- Node() - Constructor for class com.atilika.kuromoji.trie.Trie.Node
-
Constructor
- Node(char) - Constructor for class com.atilika.kuromoji.trie.Trie.Node
-
Constructor
- Node(int, float) - Constructor for class org.deeplearning4j.clustering.vptree.VPTree.Node
-
- Node2Vec<V extends SequenceElement,E extends Number> - Class in org.deeplearning4j.models.node2vec
-
Deprecated.
- Node2Vec() - Constructor for class org.deeplearning4j.models.node2vec.Node2Vec
-
Deprecated.
- Node2Vec.Builder<V extends SequenceElement,E extends Number> - Class in org.deeplearning4j.models.node2vec
-
Deprecated.
- NODE_RATIO - Static variable in class org.deeplearning4j.clustering.sptree.SpTree
-
- NodeBuilder(List<INDArray>, List<Integer>) - Constructor for class org.deeplearning4j.clustering.vptree.VPTree.NodeBuilder
-
- NodeComparator() - Constructor for class org.deeplearning4j.models.sequencevectors.graph.walkers.impl.PopularityWalker.NodeComparator
-
- NoEdgeHandling - Enum in org.deeplearning4j.graph.api
-
When walking a graph, how should we handle disconnected nodes?
i.e., those without any outgoing (directed) or undirected edges
- NoEdgeHandling - Enum in org.deeplearning4j.models.sequencevectors.graph.enums
-
This enum describes different behaviors for cases when GraphWalker don't have next hop within current walk.
- noEdgeHandling - Variable in class org.deeplearning4j.models.sequencevectors.graph.walkers.impl.RandomWalker.Builder
-
- noEdgeHandling - Variable in class org.deeplearning4j.models.sequencevectors.graph.walkers.impl.RandomWalker
-
- NoEdgesException - Exception in org.deeplearning4j.graph.exception
-
Unchecked exception, thrown to signify that an operation (usually on a vertex) cannot be completed
because there are no edges for that vertex.
- NoEdgesException() - Constructor for exception org.deeplearning4j.graph.exception.NoEdgesException
-
- NoEdgesException(String) - Constructor for exception org.deeplearning4j.graph.exception.NoEdgesException
-
- NoEdgesException(String, Exception) - Constructor for exception org.deeplearning4j.graph.exception.NoEdgesException
-
- NoEdgesException - Exception in org.deeplearning4j.models.sequencevectors.graph.exception
-
Unchecked exception, thrown to signify that an operation (usually on a vertex) cannot be completed
because there are no edges for that vertex.
- NoEdgesException() - Constructor for exception org.deeplearning4j.models.sequencevectors.graph.exception.NoEdgesException
-
- NoEdgesException(String) - Constructor for exception org.deeplearning4j.models.sequencevectors.graph.exception.NoEdgesException
-
- NoEdgesException(String, Exception) - Constructor for exception org.deeplearning4j.models.sequencevectors.graph.exception.NoEdgesException
-
- noI18NData() - Method in class org.deeplearning4j.ui.i18n.DefaultI18N
-
- noLeverageOverride - Variable in class org.deeplearning4j.nn.workspace.LayerWorkspaceMgr
-
- none() - Static method in class org.deeplearning4j.models.word2vec.VocabWord
-
- NonNegativeConstraint - Class in org.deeplearning4j.nn.conf.constraint
-
Constrain the weights to be non-negative
- NonNegativeConstraint() - Constructor for class org.deeplearning4j.nn.conf.constraint.NonNegativeConstraint
-
- NoParamLayer - Class in org.deeplearning4j.nn.conf.layers
-
- NoParamLayer(Layer.Builder) - Constructor for class org.deeplearning4j.nn.conf.layers.NoParamLayer
-
- Norm2Termination - Class in org.deeplearning4j.optimize.terminations
-
Terminate if the norm2 of the gradient is < a certain tolerance
- Norm2Termination(double) - Constructor for class org.deeplearning4j.optimize.terminations.Norm2Termination
-
- normalA(ComputationGraphConfiguration.GraphBuilder, int, String, String, String) - Static method in class org.deeplearning4j.zoo.model.helper.NASNetHelper
-
- NormalDistribution - Class in org.deeplearning4j.nn.conf.distribution
-
A normal distribution.
- NormalDistribution(double, double) - Constructor for class org.deeplearning4j.nn.conf.distribution.NormalDistribution
-
Create a normal distribution
with the given mean and std
- normalize(double, double, double) - Static method in class org.deeplearning4j.clustering.util.MathUtils
-
Normalize a value
(val - min) / (max - min)
- normalize(double[], double) - Static method in class org.deeplearning4j.clustering.util.MathUtils
-
Normalizes the doubles in the array using the given value.
- normalize(boolean) - Method in class org.deeplearning4j.plot.BarnesHutTsne.Builder
-
- normalize - Variable in class org.deeplearning4j.plot.BarnesHutTsne
-
- normalize - Variable in class org.deeplearning4j.plot.Tsne.Builder
-
- normalize(boolean) - Method in class org.deeplearning4j.plot.Tsne.Builder
-
- normalize - Variable in class org.deeplearning4j.plot.Tsne
-
- normalized - Variable in class org.deeplearning4j.models.embeddings.reader.impl.BasicModelUtils
-
- normalizedLabels - Variable in class org.deeplearning4j.models.paragraphvectors.ParagraphVectors
-
- NORMALIZER_BIN - Static variable in class org.deeplearning4j.util.ModelSerializer
-
- normalizeToOne(double[]) - Static method in class org.deeplearning4j.clustering.util.MathUtils
-
- notify(StatsStorageEvent) - Method in interface org.deeplearning4j.api.storage.StatsStorageListener
-
Notify will be called whenever an event (new information posted, etc) occurs.
- notify(StatsStorageEvent) - Method in class org.deeplearning4j.ui.storage.impl.QueuePairStatsStorageListener
-
- notify(StatsStorageEvent) - Method in class org.deeplearning4j.ui.storage.impl.QueueStatsStorageListener
-
- notifyListeners(List<StatsStorageEvent>) - Method in class org.deeplearning4j.ui.storage.BaseCollectionStatsStorage
-
- notifyListeners(List<StatsStorageEvent>) - Method in class org.deeplearning4j.ui.storage.sqlite.J7FileStatsStorage
-
- nOut(int) - Method in class org.deeplearning4j.nn.conf.layers.CnnLossLayer.Builder
-
- nOut - Variable in class org.deeplearning4j.nn.conf.layers.FeedForwardLayer.Builder
-
- nOut(int) - Method in class org.deeplearning4j.nn.conf.layers.FeedForwardLayer.Builder
-
Number of outputs - used to set the layer size (number of units/nodes for the current layer).
- nOut - Variable in class org.deeplearning4j.nn.conf.layers.FeedForwardLayer
-
- nOut(int) - Method in class org.deeplearning4j.nn.conf.layers.LossLayer.Builder
-
- nOut(int) - Method in class org.deeplearning4j.nn.conf.layers.RnnLossLayer.Builder
-
- nOut(int) - Method in class org.deeplearning4j.nn.conf.layers.variational.VariationalAutoencoder.Builder
-
Set the size of the VAE state Z.
- nOut(int) - Method in class org.deeplearning4j.nn.conf.ocnn.OCNNOutputLayer.Builder
-
- nOutReplace(int, int, WeightInit) - Method in class org.deeplearning4j.nn.transferlearning.TransferLearning.Builder
-
Modify the architecture of a layer by changing nOut
Note this will also affect the layer that follows the layer specified, unless it is the output layer
- nOutReplace(int, int, Distribution) - Method in class org.deeplearning4j.nn.transferlearning.TransferLearning.Builder
-
Modify the architecture of a layer by changing nOut
Note this will also affect the layer that follows the layer specified, unless it is the output layer
- nOutReplace(int, int, WeightInit, WeightInit) - Method in class org.deeplearning4j.nn.transferlearning.TransferLearning.Builder
-
Modify the architecture of a layer by changing nOut
Note this will also affect the layer that follows the layer specified, unless it is the output layer
Can specify different weight init schemes for the specified layer and the layer that follows it.
- nOutReplace(int, int, Distribution, Distribution) - Method in class org.deeplearning4j.nn.transferlearning.TransferLearning.Builder
-
Modify the architecture of a layer by changing nOut
Note this will also affect the layer that follows the layer specified, unless it is the output layer
Can specify different weight init schemes for the specified layer and the layer that follows it.
- nOutReplace(int, int, WeightInit, Distribution) - Method in class org.deeplearning4j.nn.transferlearning.TransferLearning.Builder
-
Modify the architecture of a layer by changing nOut
Note this will also affect the layer that follows the layer specified, unless it is the output layer
Can specify different weight init schemes for the specified layer and the layer that follows it.
- nOutReplace(int, int, Distribution, WeightInit) - Method in class org.deeplearning4j.nn.transferlearning.TransferLearning.Builder
-
Modify the architecture of a layer by changing nOut
Note this will also affect the layer that follows the layer specified, unless it is the output layer
Can specify different weight init schemes for the specified layer and the layer that follows it.
- nOutReplace(String, int, WeightInit) - Method in class org.deeplearning4j.nn.transferlearning.TransferLearning.GraphBuilder
-
Modify the architecture of a vertex layer by changing nOut
Note this will also affect the vertex layer that follows the layer specified, unless it is the output layer
Currently does not support modifying nOut of layers that feed into non-layer vertices like merge, subset etc
To modify nOut for such vertices use remove vertex, followed by add vertex
Can specify different weight init schemes for the specified layer and the layer that follows it.
- nOutReplace(String, int, Distribution) - Method in class org.deeplearning4j.nn.transferlearning.TransferLearning.GraphBuilder
-
Modify the architecture of a vertex layer by changing nOut
Note this will also affect the vertex layer that follows the layer specified, unless it is the output layer
Currently does not support modifying nOut of layers that feed into non-layer vertices like merge, subset etc
To modify nOut for such vertices use remove vertex, followed by add vertex
Can specify different weight init schemes for the specified layer and the layer that follows it.
- nOutReplace(String, int, Distribution, Distribution) - Method in class org.deeplearning4j.nn.transferlearning.TransferLearning.GraphBuilder
-
Modified nOut of specified layer.
- nOutReplace(String, int, WeightInit, Distribution) - Method in class org.deeplearning4j.nn.transferlearning.TransferLearning.GraphBuilder
-
- nOutReplace(String, int, Distribution, WeightInit) - Method in class org.deeplearning4j.nn.transferlearning.TransferLearning.GraphBuilder
-
- nOutReplace(String, int, WeightInit, WeightInit) - Method in class org.deeplearning4j.nn.transferlearning.TransferLearning.GraphBuilder
-
- noWorkspaceFor(ArrayType) - Method in class org.deeplearning4j.nn.workspace.LayerWorkspaceMgr.Builder
-
Specify that no workspace should be used for array of the specified type - i.e., these arrays should all
be scoped out.
- noWorkspaces() - Static method in class org.deeplearning4j.nn.workspace.LayerWorkspaceMgr
-
- noWorkspacesImmutable() - Static method in class org.deeplearning4j.nn.workspace.LayerWorkspaceMgr
-
- NR - Static variable in class org.ansj.domain.Nature
-
- NR - Static variable in class org.ansj.domain.TermNature
-
- NR - Static variable in class org.ansj.domain.TermNatures
-
- NRF - Static variable in class org.ansj.domain.Nature
-
- NRF - Static variable in class org.ansj.domain.TermNature
-
- NRF - Static variable in class org.ansj.domain.TermNatures
-
- NS - Static variable in class org.ansj.domain.TermNature
-
- NS - Static variable in class org.ansj.domain.TermNatures
-
- NT - Static variable in class org.ansj.domain.TermNature
-
- NT - Static variable in class org.ansj.domain.TermNatures
-
- NTP_SOURCE_SERVER_PROPERTY - Static variable in class org.deeplearning4j.spark.time.NTPTimeSource
-
- NTP_SOURCE_UPDATE_FREQUENCY_MS_PROPERTY - Static variable in class org.deeplearning4j.spark.time.NTPTimeSource
-
- NTPTimeSource - Class in org.deeplearning4j.spark.time
-
A
TimeSource that utilize Network Time Protocol to determine the system clock offset
Instances should be obtained via
NTPTimeSource.getInstance() or
TimeSourceProvider; one instance may be
used per machine
Specifically, the implementation uses Apache Commons Net (already a dependency in Spark) to query a NTP server.
- nu - Variable in class org.deeplearning4j.nn.conf.ocnn.OCNNOutputLayer.Builder
-
- nu(double) - Method in class org.deeplearning4j.nn.conf.ocnn.OCNNOutputLayer.Builder
-
- NU_KEY - Static variable in class org.deeplearning4j.nn.layers.ocnn.OCNNParamInitializer
-
- NULL - Static variable in class org.ansj.domain.AnsjItem
-
- NULL - Static variable in class org.ansj.domain.Nature
-
- NULL - Static variable in class org.ansj.domain.NumNatureAttr
-
- NULL - Static variable in class org.ansj.domain.PersonNatureAttr
-
- NULL - Static variable in class org.ansj.domain.TermNature
-
- NULL - Static variable in class org.ansj.domain.TermNatures
-
- nullDataSet - Variable in class org.deeplearning4j.parallelism.trainer.DefaultTrainer
-
- nullMode - Variable in class org.deeplearning4j.parallelism.trainer.DefaultTrainer
-
- NUM_BEGIN - Static variable in class org.ansj.app.crf.Config
-
- NUM_EXAMPLES - Static variable in class org.deeplearning4j.datasets.fetchers.IrisDataFetcher
-
- NUM_EXAMPLES - Static variable in class org.deeplearning4j.datasets.fetchers.MnistDataFetcher
-
- NUM_EXAMPLES - Static variable in class org.deeplearning4j.datasets.fetchers.TinyImageNetFetcher
-
- NUM_EXAMPLES - Static variable in class org.deeplearning4j.datasets.fetchers.UciSequenceDataFetcher
-
- NUM_EXAMPLES_TEST - Static variable in class org.deeplearning4j.datasets.fetchers.MnistDataFetcher
-
- NUM_LABELS - Static variable in class org.deeplearning4j.datasets.fetchers.SvhnDataFetcher
-
- NUM_LABELS - Static variable in class org.deeplearning4j.datasets.fetchers.TinyImageNetFetcher
-
- NUM_LABELS - Static variable in class org.deeplearning4j.datasets.fetchers.UciSequenceDataFetcher
-
- NUM_LAYERS - Static variable in class org.deeplearning4j.nn.layers.recurrent.CudnnLSTMHelper
-
- NUM_LINEAR_LAYERS - Static variable in class org.deeplearning4j.nn.layers.recurrent.CudnnLSTMHelper
-
- NUM_WORDS - Static variable in class org.deeplearning4j.spark.models.embeddings.word2vec.Word2VecPerformerVoid
-
Deprecated.
- NUM_WORDS - Static variable in class org.deeplearning4j.spark.models.embeddings.word2vec.Word2VecVariables
-
Deprecated.
- numAttr - Variable in class org.ansj.domain.TermNatures
-
数字属性
- numberOfBuckets - Variable in class org.deeplearning4j.parallelism.MagicQueue
-
Deprecated.
- numberOfWorkersPerNode - Variable in class org.deeplearning4j.spark.parameterserver.conf.SharedTrainingConfiguration
-
- numChannels - Variable in class org.deeplearning4j.nn.conf.preprocessor.Cnn3DToFeedForwardPreProcessor
-
- numChannels - Variable in class org.deeplearning4j.nn.conf.preprocessor.CnnToFeedForwardPreProcessor
-
- numChannels(int[]) - Static method in class org.deeplearning4j.util.ConvolutionUtils
-
Returns the number of
feature maps for a given shape (must be at least 3 dimensions
- numClasses() - Method in class org.deeplearning4j.eval.Evaluation
-
- numClasses() - Method in class org.deeplearning4j.eval.EvaluationCalibration
-
- numColumns() - Method in class org.deeplearning4j.eval.RegressionEvaluation
-
- numDimension(int) - Method in class org.deeplearning4j.plot.BarnesHutTsne.Builder
-
- numDocuments() - Method in interface org.deeplearning4j.text.invertedindex.InvertedIndex
-
Returns the number of documents
- numElementsDrained - Variable in class org.deeplearning4j.optimize.solvers.accumulation.FancyBlockingQueue
-
- numElementsReady - Variable in class org.deeplearning4j.optimize.solvers.accumulation.FancyBlockingQueue
-
- numEndFreq - Variable in class org.ansj.domain.NumNatureAttr
-
- numEpochs - Variable in class org.deeplearning4j.datasets.iterator.MultipleEpochsIterator
-
Deprecated.
- numEpochs - Variable in class org.deeplearning4j.models.embeddings.wordvectors.WordVectorsImpl
-
- numEpochs - Variable in class org.deeplearning4j.models.sequencevectors.SequenceVectors.Builder
-
- numEpochs - Variable in class org.deeplearning4j.spark.models.embeddings.word2vec.Word2Vec.Builder
-
- numExamples() - Method in class org.deeplearning4j.datasets.datavec.RecordReaderDataSetIterator
-
- numExamples() - Method in class org.deeplearning4j.datasets.datavec.SequenceRecordReaderDataSetIterator
-
- numExamples() - Method in class org.deeplearning4j.datasets.iterator.AbstractDataSetIterator
-
Total number of examples in the dataset
- numExamples() - Method in class org.deeplearning4j.datasets.iterator.AsyncDataSetIterator
-
Total number of examples in the dataset
- numExamples() - Method in class org.deeplearning4j.datasets.iterator.AsyncShieldDataSetIterator
-
Total number of examples in the dataset
- numExamples - Variable in class org.deeplearning4j.datasets.iterator.BaseDatasetIterator
-
- numExamples() - Method in class org.deeplearning4j.datasets.iterator.BaseDatasetIterator
-
- numExamples() - Method in class org.deeplearning4j.datasets.iterator.EarlyTerminationDataSetIterator
-
- numExamples() - Method in class org.deeplearning4j.datasets.iterator.ExistingDataSetIterator
-
- numExamples() - Method in class org.deeplearning4j.datasets.iterator.file.FileDataSetIterator
-
- numExamples() - Method in class org.deeplearning4j.datasets.iterator.FileSplitDataSetIterator
-
- numExamples() - Method in class org.deeplearning4j.datasets.iterator.impl.BenchmarkDataSetIterator
-
- numExamples - Variable in class org.deeplearning4j.datasets.iterator.impl.CifarDataSetIterator
-
- numExamples - Variable in class org.deeplearning4j.datasets.iterator.impl.EmnistDataSetIterator
-
- numExamples() - Method in class org.deeplearning4j.datasets.iterator.impl.ListDataSetIterator
-
- numExamples() - Method in class org.deeplearning4j.datasets.iterator.IteratorDataSetIterator
-
- numExamples() - Method in class org.deeplearning4j.datasets.iterator.MultiDataSetWrapperIterator
-
- numExamples() - Method in class org.deeplearning4j.datasets.iterator.MultipleEpochsIterator
-
Deprecated.
Total number of examples in the dataset
- numExamples() - Method in class org.deeplearning4j.datasets.iterator.parallel.BaseParallelDataSetIterator
-
- numExamples() - Method in class org.deeplearning4j.datasets.iterator.ReconstructionDataSetIterator
-
Total number of examples in the dataset
- numExamples() - Method in class org.deeplearning4j.datasets.iterator.SamplingDataSetIterator
-
- numExamples() - Method in class org.deeplearning4j.datasets.iterator.WorkspacesShieldDataSetIterator
-
- numExamples() - Method in class org.deeplearning4j.datasets.test.TestDataSetIterator
-
- numExamples() - Method in class org.deeplearning4j.iterator.CnnSentenceDataSetIterator
-
- numExamples() - Method in class org.deeplearning4j.models.word2vec.iterator.Word2VecDataSetIterator
-
- numExamples() - Method in class org.deeplearning4j.spark.iterator.BaseDataSetIterator
-
- numExamples() - Method in class org.deeplearning4j.spark.parameterserver.iterators.VirtualDataSetIterator
-
- numExamplesTest(EmnistDataSetIterator.Set) - Static method in class org.deeplearning4j.datasets.iterator.impl.EmnistDataSetIterator
-
Get the number of test examples for the specified subset
- numExamplesTrain(EmnistDataSetIterator.Set) - Static method in class org.deeplearning4j.datasets.iterator.impl.EmnistDataSetIterator
-
Get the number of training examples for the specified subset
- numFeatureMap(NeuralNetConfiguration) - Static method in class org.deeplearning4j.util.ConvolutionUtils
-
- numFreq - Variable in class org.ansj.domain.NumNatureAttr
-
- numHistogramBins(StatsType) - Method in interface org.deeplearning4j.ui.stats.api.StatsUpdateConfiguration
-
- numHistogramBins(int) - Method in class org.deeplearning4j.ui.stats.impl.DefaultStatsUpdateConfiguration.Builder
-
- numHistogramBins(StatsType) - Method in class org.deeplearning4j.ui.stats.impl.DefaultStatsUpdateConfiguration
-
- numInGroup() - Method in class org.deeplearning4j.ui.stats.sbe.GroupSizeEncodingDecoder
-
- numInGroup(int) - Method in class org.deeplearning4j.ui.stats.sbe.GroupSizeEncodingEncoder
-
- numInGroupMaxValue() - Static method in class org.deeplearning4j.ui.stats.sbe.GroupSizeEncodingDecoder
-
- numInGroupMaxValue() - Static method in class org.deeplearning4j.ui.stats.sbe.GroupSizeEncodingEncoder
-
- numInGroupMinValue() - Static method in class org.deeplearning4j.ui.stats.sbe.GroupSizeEncodingDecoder
-
- numInGroupMinValue() - Static method in class org.deeplearning4j.ui.stats.sbe.GroupSizeEncodingEncoder
-
- numInGroupNullValue() - Static method in class org.deeplearning4j.ui.stats.sbe.GroupSizeEncodingDecoder
-
- numInGroupNullValue() - Static method in class org.deeplearning4j.ui.stats.sbe.GroupSizeEncodingEncoder
-
- numIterations - Variable in class org.deeplearning4j.models.embeddings.wordvectors.WordVectorsImpl
-
- numIterations - Variable in class org.deeplearning4j.spark.models.embeddings.word2vec.Word2Vec.Builder
-
- numLabelClasses() - Method in interface org.deeplearning4j.iterator.LabeledSentenceProvider
-
Equivalent to allLabels().size()
- numLabelClasses() - Method in class org.deeplearning4j.iterator.provider.CollectionLabeledSentenceProvider
-
- numLabelClasses() - Method in class org.deeplearning4j.iterator.provider.FileLabeledSentenceProvider
-
- numLabelClasses() - Method in class org.deeplearning4j.iterator.provider.LabelAwareConverter
-
- numLabels(EmnistDataSetIterator.Set) - Static method in class org.deeplearning4j.base.EmnistFetcher
-
- numLabels(EmnistDataSetIterator.Set) - Static method in class org.deeplearning4j.datasets.iterator.impl.EmnistDataSetIterator
-
Get the number of labels for the specified subset
- numLabels() - Method in class org.deeplearning4j.eval.EvaluationBinary
-
Returns the number of labels - (i.e., size of the prediction/labels arrays) - if known.
- numLabels() - Method in class org.deeplearning4j.eval.ROCBinary
-
Returns the number of labels - (i.e., size of the prediction/labels arrays) - if known.
- numLabels() - Method in interface org.deeplearning4j.nn.api.Classifier
-
Returns the number of possible labels
- numLabels() - Method in class org.deeplearning4j.nn.layers.BaseOutputLayer
-
Returns the number of possible labels
- numLabels() - Method in class org.deeplearning4j.nn.layers.convolution.CnnLossLayer
-
- numLabels() - Method in class org.deeplearning4j.nn.layers.LossLayer
-
Returns the number of possible labels
- numLabels() - Method in class org.deeplearning4j.nn.layers.objdetect.Yolo2OutputLayer
-
- numLabels() - Method in class org.deeplearning4j.nn.layers.recurrent.RnnLossLayer
-
- numLabels() - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
-
Returns the number of possible labels
- NumNatureAttr - Class in org.ansj.domain
-
- NumNatureAttr() - Constructor for class org.ansj.domain.NumNatureAttr
-
- numObjectsEachWorker(int) - Method in class org.deeplearning4j.spark.impl.paramavg.ParameterAveragingTrainingMaster
-
- numObjectsEachWorker(int) - Method in class org.deeplearning4j.spark.parameterserver.training.SharedTrainingMaster
-
- numParams() - Method in interface org.deeplearning4j.nn.api.Model
-
the number of parameters for the model
- numParams(boolean) - Method in interface org.deeplearning4j.nn.api.Model
-
the number of parameters for the model
- numParams(NeuralNetConfiguration) - Method in interface org.deeplearning4j.nn.api.ParamInitializer
-
- numParams(Layer) - Method in interface org.deeplearning4j.nn.api.ParamInitializer
-
- numParams(boolean) - Method in class org.deeplearning4j.nn.conf.graph.ElementWiseVertex
-
- numParams(boolean) - Method in class org.deeplearning4j.nn.conf.graph.FrozenVertex
-
- numParams(boolean) - Method in class org.deeplearning4j.nn.conf.graph.GraphVertex
-
- numParams(boolean) - Method in class org.deeplearning4j.nn.conf.graph.L2NormalizeVertex
-
- numParams(boolean) - Method in class org.deeplearning4j.nn.conf.graph.L2Vertex
-
- numParams(boolean) - Method in class org.deeplearning4j.nn.conf.graph.LayerVertex
-
- numParams(boolean) - Method in class org.deeplearning4j.nn.conf.graph.MergeVertex
-
- numParams(boolean) - Method in class org.deeplearning4j.nn.conf.graph.PoolHelperVertex
-
- numParams(boolean) - Method in class org.deeplearning4j.nn.conf.graph.PreprocessorVertex
-
- numParams(boolean) - Method in class org.deeplearning4j.nn.conf.graph.ReshapeVertex
-
- numParams(boolean) - Method in class org.deeplearning4j.nn.conf.graph.rnn.DuplicateToTimeSeriesVertex
-
- numParams(boolean) - Method in class org.deeplearning4j.nn.conf.graph.rnn.LastTimeStepVertex
-
- numParams(boolean) - Method in class org.deeplearning4j.nn.conf.graph.rnn.ReverseTimeSeriesVertex
-
- numParams(boolean) - Method in class org.deeplearning4j.nn.conf.graph.ScaleVertex
-
- numParams(boolean) - Method in class org.deeplearning4j.nn.conf.graph.ShiftVertex
-
- numParams(boolean) - Method in class org.deeplearning4j.nn.conf.graph.StackVertex
-
- numParams(boolean) - Method in class org.deeplearning4j.nn.conf.graph.SubsetVertex
-
- numParams(boolean) - Method in class org.deeplearning4j.nn.conf.graph.UnstackVertex
-
- numParams() - Method in class org.deeplearning4j.nn.graph.ComputationGraph
-
- numParams(boolean) - Method in class org.deeplearning4j.nn.graph.ComputationGraph
-
- numParams() - Method in class org.deeplearning4j.nn.layers.AbstractLayer
-
The number of parameters for the model
- numParams(boolean) - Method in class org.deeplearning4j.nn.layers.AbstractLayer
-
- numParams() - Method in class org.deeplearning4j.nn.layers.BaseLayer
-
The number of parameters for the model
- numParams(boolean) - Method in class org.deeplearning4j.nn.layers.BasePretrainNetwork
-
- numParams() - Method in class org.deeplearning4j.nn.layers.BasePretrainNetwork
-
The number of parameters for the model, for backprop (i.e., excluding visible bias)
- numParams() - Method in class org.deeplearning4j.nn.layers.convolution.SpaceToBatch
-
- numParams() - Method in class org.deeplearning4j.nn.layers.convolution.SpaceToDepth
-
- numParams() - Method in class org.deeplearning4j.nn.layers.convolution.subsampling.Subsampling3DLayer
-
- numParams() - Method in class org.deeplearning4j.nn.layers.convolution.subsampling.SubsamplingLayer
-
- numParams() - Method in class org.deeplearning4j.nn.layers.convolution.upsampling.Upsampling2D
-
- numParams() - Method in class org.deeplearning4j.nn.layers.convolution.upsampling.Upsampling3D
-
- numParams(NeuralNetConfiguration) - Method in class org.deeplearning4j.nn.layers.ocnn.OCNNParamInitializer
-
- numParams(Layer) - Method in class org.deeplearning4j.nn.layers.ocnn.OCNNParamInitializer
-
- numParams() - Method in class org.deeplearning4j.nn.layers.recurrent.BidirectionalLayer
-
- numParams(boolean) - Method in class org.deeplearning4j.nn.layers.recurrent.BidirectionalLayer
-
- numParams() - Method in class org.deeplearning4j.nn.layers.recurrent.MaskZeroLayer
-
- numParams() - Method in class org.deeplearning4j.nn.layers.variational.VariationalAutoencoder
-
- numParams(boolean) - Method in class org.deeplearning4j.nn.layers.variational.VariationalAutoencoder
-
- numParams() - Method in class org.deeplearning4j.nn.layers.wrapper.BaseWrapperLayer
-
- numParams(boolean) - Method in class org.deeplearning4j.nn.layers.wrapper.BaseWrapperLayer
-
- numParams() - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
-
Returns a 1 x m vector where the vector is composed of
a flattened vector of all of the weights for the
various neuralNets and output layer
- numParams(boolean) - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
-
- numParams(NeuralNetConfiguration) - Method in class org.deeplearning4j.nn.params.BatchNormalizationParamInitializer
-
- numParams(Layer) - Method in class org.deeplearning4j.nn.params.BatchNormalizationParamInitializer
-
- numParams(NeuralNetConfiguration) - Method in class org.deeplearning4j.nn.params.BidirectionalParamInitializer
-
- numParams(Layer) - Method in class org.deeplearning4j.nn.params.BidirectionalParamInitializer
-
- numParams(NeuralNetConfiguration) - Method in class org.deeplearning4j.nn.params.CenterLossParamInitializer
-
- numParams(NeuralNetConfiguration) - Method in class org.deeplearning4j.nn.params.Convolution3DParamInitializer
-
- numParams(Layer) - Method in class org.deeplearning4j.nn.params.Convolution3DParamInitializer
-
- numParams(NeuralNetConfiguration) - Method in class org.deeplearning4j.nn.params.ConvolutionParamInitializer
-
- numParams(Layer) - Method in class org.deeplearning4j.nn.params.ConvolutionParamInitializer
-
- numParams(NeuralNetConfiguration) - Method in class org.deeplearning4j.nn.params.DefaultParamInitializer
-
- numParams(Layer) - Method in class org.deeplearning4j.nn.params.DefaultParamInitializer
-
- numParams(NeuralNetConfiguration) - Method in class org.deeplearning4j.nn.params.DepthwiseConvolutionParamInitializer
-
- numParams(Layer) - Method in class org.deeplearning4j.nn.params.DepthwiseConvolutionParamInitializer
-
- numParams(Layer) - Method in class org.deeplearning4j.nn.params.ElementWiseParamInitializer
-
- numParams(NeuralNetConfiguration) - Method in class org.deeplearning4j.nn.params.EmptyParamInitializer
-
- numParams(Layer) - Method in class org.deeplearning4j.nn.params.EmptyParamInitializer
-
- numParams(NeuralNetConfiguration) - Method in class org.deeplearning4j.nn.params.FrozenLayerParamInitializer
-
- numParams(Layer) - Method in class org.deeplearning4j.nn.params.FrozenLayerParamInitializer
-
- numParams(NeuralNetConfiguration) - Method in class org.deeplearning4j.nn.params.FrozenLayerWithBackpropParamInitializer
-
- numParams(Layer) - Method in class org.deeplearning4j.nn.params.FrozenLayerWithBackpropParamInitializer
-
- numParams(NeuralNetConfiguration) - Method in class org.deeplearning4j.nn.params.GravesBidirectionalLSTMParamInitializer
-
- numParams(Layer) - Method in class org.deeplearning4j.nn.params.GravesBidirectionalLSTMParamInitializer
-
- numParams(NeuralNetConfiguration) - Method in class org.deeplearning4j.nn.params.GravesLSTMParamInitializer
-
- numParams(Layer) - Method in class org.deeplearning4j.nn.params.GravesLSTMParamInitializer
-
- numParams(NeuralNetConfiguration) - Method in class org.deeplearning4j.nn.params.LSTMParamInitializer
-
- numParams(Layer) - Method in class org.deeplearning4j.nn.params.LSTMParamInitializer
-
- numParams(NeuralNetConfiguration) - Method in class org.deeplearning4j.nn.params.PretrainParamInitializer
-
- numParams(NeuralNetConfiguration) - Method in class org.deeplearning4j.nn.params.SameDiffParamInitializer
-
- numParams(Layer) - Method in class org.deeplearning4j.nn.params.SameDiffParamInitializer
-
- numParams(NeuralNetConfiguration) - Method in class org.deeplearning4j.nn.params.SeparableConvolutionParamInitializer
-
- numParams(Layer) - Method in class org.deeplearning4j.nn.params.SeparableConvolutionParamInitializer
-
- numParams(NeuralNetConfiguration) - Method in class org.deeplearning4j.nn.params.SimpleRnnParamInitializer
-
- numParams(Layer) - Method in class org.deeplearning4j.nn.params.SimpleRnnParamInitializer
-
- numParams(NeuralNetConfiguration) - Method in class org.deeplearning4j.nn.params.VariationalAutoencoderParamInitializer
-
- numParams(NeuralNetConfiguration) - Method in class org.deeplearning4j.nn.params.WrapperLayerParamInitializer
-
- numParams(Layer) - Method in class org.deeplearning4j.nn.params.WrapperLayerParamInitializer
-
- numParams() - Method in class org.deeplearning4j.plot.BarnesHutTsne
-
- numParams(boolean) - Method in class org.deeplearning4j.plot.BarnesHutTsne
-
- numPartitions() - Method in class org.deeplearning4j.spark.data.shuffle.IntPartitioner
-
Deprecated.
- numPartitions() - Method in class org.deeplearning4j.spark.impl.common.repartition.BalancedPartitioner
-
- numPartitions() - Method in class org.deeplearning4j.spark.impl.common.repartition.HashingBalancedPartitioner
-
- numPoints() - Method in class org.deeplearning4j.eval.curves.BaseCurve
-
- numPoints() - Method in class org.deeplearning4j.eval.curves.BaseHistogram
-
- numPoints() - Method in class org.deeplearning4j.eval.curves.Histogram
-
- numPoints() - Method in class org.deeplearning4j.eval.curves.PrecisionRecallCurve
-
- numPoints() - Method in class org.deeplearning4j.eval.curves.ReliabilityDiagram
-
- numPoints() - Method in class org.deeplearning4j.eval.curves.RocCurve
-
- numPossibleLabels - Variable in class org.deeplearning4j.datasets.datavec.RecordReaderDataSetIterator.Builder
-
- numPossibleLabels - Variable in class org.deeplearning4j.datasets.datavec.RecordReaderDataSetIterator
-
- numProducers - Variable in class org.deeplearning4j.datasets.iterator.parallel.BaseParallelDataSetIterator
-
- NumRecognition - Class in org.ansj.recognition.arrimpl
-
- NumRecognition() - Constructor for class org.ansj.recognition.arrimpl.NumRecognition
-
- numRowCounter - Variable in class org.deeplearning4j.eval.Evaluation
-
- numSamples(int) - Method in class org.deeplearning4j.nn.conf.layers.variational.VariationalAutoencoder.Builder
-
Set the number of samples per data point (from VAE state Z) used when doing pretraining.
- numSamples - Variable in class org.deeplearning4j.nn.layers.variational.VariationalAutoencoder
-
- numTest - Variable in class org.deeplearning4j.datasets.iterator.DataSetIteratorSplitter
-
- numTest - Variable in class org.deeplearning4j.datasets.iterator.MultiDataSetIteratorSplitter
-
- numTrain - Variable in class org.deeplearning4j.datasets.iterator.DataSetIteratorSplitter
-
- numTrain - Variable in class org.deeplearning4j.datasets.iterator.MultiDataSetIteratorSplitter
-
- numTrainableParams - Variable in class org.deeplearning4j.nn.modelimport.keras.layers.convolutional.KerasConvolution
-
- numVertices() - Method in interface org.deeplearning4j.graph.api.IGraph
-
Number of vertices in the graph
- numVertices() - Method in class org.deeplearning4j.graph.graph.Graph
-
- numVertices() - Method in class org.deeplearning4j.graph.models.embeddings.GraphVectorsImpl
-
- numVertices() - Method in interface org.deeplearning4j.graph.models.GraphVectors
-
- numVertices() - Method in class org.deeplearning4j.models.sequencevectors.graph.primitives.Graph
-
- numVertices() - Method in interface org.deeplearning4j.models.sequencevectors.graph.primitives.IGraph
-
Number of vertices in the graph
- numWords - Variable in class org.deeplearning4j.models.embeddings.loader.WordVectorSerializer.BinaryReader
-
- numWords() - Method in class org.deeplearning4j.models.word2vec.wordstore.inmemory.AbstractCache
-
Returns number of elements in this vocabulary
- numWords() - Method in class org.deeplearning4j.models.word2vec.wordstore.inmemory.InMemoryLookupCache
-
Deprecated.
Returns the number of words in the cache
- numWords() - Method in interface org.deeplearning4j.models.word2vec.wordstore.VocabCache
-
Returns the number of words in the cache
- numWords() - Method in class org.deeplearning4j.models.word2vec.wordstore.VocabularyHolder
-
- numWords(int) - Method in class org.deeplearning4j.spark.models.embeddings.word2vec.Word2VecParam.Builder
-
Deprecated.
- numWordsEncountered() - Method in class org.deeplearning4j.bagofwords.vectorizer.BaseTextVectorizer
-
Returns the number of words encountered so far
- numWordsEncountered() - Method in interface org.deeplearning4j.bagofwords.vectorizer.TextVectorizer
-
Returns the number of words encountered so far
- numWorkers - Variable in class org.deeplearning4j.spark.impl.paramavg.ParameterAveragingTrainingMaster.Builder
-
- numWorkers - Variable in class org.deeplearning4j.spark.impl.paramavg.ParameterAveragingTrainingMaster
-
- numWorkers - Variable in class org.deeplearning4j.spark.parameterserver.training.SharedTrainingMaster.Builder
-
- numWorkers - Variable in class org.deeplearning4j.spark.parameterserver.training.SharedTrainingMaster
-
- numWorkersPerNode - Variable in class org.deeplearning4j.spark.parameterserver.training.SharedTrainingMaster.Builder
-
- numWorkersPerNode - Variable in class org.deeplearning4j.spark.parameterserver.training.SharedTrainingMaster
-
- nVertices - Variable in class org.deeplearning4j.graph.models.embeddings.InMemoryGraphLookupTable
-
- NW - Static variable in class org.ansj.domain.Nature
-
- NW - Static variable in class org.ansj.domain.TermNature
-
- NW - Static variable in class org.ansj.domain.TermNatures
-
- padding(int) - Method in class org.deeplearning4j.nn.conf.layers.Convolution1DLayer.Builder
-
- padding(int...) - Method in class org.deeplearning4j.nn.conf.layers.Convolution3D.Builder
-
Set padding size for 3D convolutions in (depth, height, width) order
- padding - Variable in class org.deeplearning4j.nn.conf.layers.ConvolutionLayer.BaseConvBuilder
-
- padding(int...) - Method in class org.deeplearning4j.nn.conf.layers.ConvolutionLayer.Builder
-
- padding - Variable in class org.deeplearning4j.nn.conf.layers.ConvolutionLayer
-
- padding(int...) - Method in class org.deeplearning4j.nn.conf.layers.Deconvolution2D.Builder
-
- padding(int...) - Method in class org.deeplearning4j.nn.conf.layers.DepthwiseConvolution2D.Builder
-
- padding(int...) - Method in class org.deeplearning4j.nn.conf.layers.SeparableConvolution2D.Builder
-
- padding - Variable in class org.deeplearning4j.nn.conf.layers.SpaceToBatchLayer.Builder
-
- padding(int[][]) - Method in class org.deeplearning4j.nn.conf.layers.SpaceToBatchLayer.Builder
-
- padding - Variable in class org.deeplearning4j.nn.conf.layers.SpaceToBatchLayer
-
- padding(int) - Method in class org.deeplearning4j.nn.conf.layers.Subsampling1DLayer.Builder
-
Padding
- padding - Variable in class org.deeplearning4j.nn.conf.layers.Subsampling3DLayer.BaseSubsamplingBuilder
-
- padding(int...) - Method in class org.deeplearning4j.nn.conf.layers.Subsampling3DLayer.Builder
-
Padding
- padding - Variable in class org.deeplearning4j.nn.conf.layers.Subsampling3DLayer
-
- padding - Variable in class org.deeplearning4j.nn.conf.layers.SubsamplingLayer.BaseSubsamplingBuilder
-
- padding(int...) - Method in class org.deeplearning4j.nn.conf.layers.SubsamplingLayer.Builder
-
Padding
- padding - Variable in class org.deeplearning4j.nn.conf.layers.SubsamplingLayer
-
- paginate(String, BucketKeyListener) - Method in class org.deeplearning4j.aws.s3.reader.S3Downloader
-
Paginates through a bucket's keys invoking the listener
at each key
- PairDataSetToMultiDataSetFn<K> - Class in org.deeplearning4j.spark.impl.graph.dataset
-
Simple conversion function to convert from a JavaPairRDD<K,DataSet> to a JavaPairRDD<K,MultiDataSet>
- PairDataSetToMultiDataSetFn() - Constructor for class org.deeplearning4j.spark.impl.graph.dataset.PairDataSetToMultiDataSetFn
-
- PairToArrayPair<K> - Class in org.deeplearning4j.spark.impl.graph.scoring
-
Simple conversion function for SparkComputationGraph
- PairToArrayPair() - Constructor for class org.deeplearning4j.spark.impl.graph.scoring.PairToArrayPair
-
- ParagraphVectors - Class in org.deeplearning4j.models.paragraphvectors
-
Basic ParagraphVectors (aka Doc2Vec) implementation for DL4j, as wrapper over SequenceVectors
- ParagraphVectors() - Constructor for class org.deeplearning4j.models.paragraphvectors.ParagraphVectors
-
- ParagraphVectors.BlindInferenceCallable - Class in org.deeplearning4j.models.paragraphvectors
-
- ParagraphVectors.Builder - Class in org.deeplearning4j.models.paragraphvectors
-
- ParagraphVectors.InferenceCallable - Class in org.deeplearning4j.models.paragraphvectors
-
- parallelCounter() - Static method in class org.deeplearning4j.text.movingwindow.Util
-
Returns a thread safe counter
- parallelCounterMap() - Static method in class org.deeplearning4j.text.movingwindow.Util
-
Returns a thread safe counter map
- ParallelInference - Class in org.deeplearning4j.parallelism
-
This class is simple wrapper for
ParallelInference using batched input
- ParallelInference() - Constructor for class org.deeplearning4j.parallelism.ParallelInference
-
- ParallelInference.Builder - Class in org.deeplearning4j.parallelism
-
- ParallelInference.ObservablesProvider - Class in org.deeplearning4j.parallelism
-
- parallelTasks(List<Runnable>, ExecutorService) - Static method in class org.deeplearning4j.clustering.util.MultiThreadUtils
-
- ParallelTransformerIterator - Class in org.deeplearning4j.models.sequencevectors.transformers.impl.iterables
-
TransformerIterator implementation that's does transformation/tokenization/normalization/whatever in parallel threads.
- ParallelTransformerIterator(LabelAwareIterator, SentenceTransformer) - Constructor for class org.deeplearning4j.models.sequencevectors.transformers.impl.iterables.ParallelTransformerIterator
-
- ParallelTransformerIterator(LabelAwareIterator, SentenceTransformer, boolean) - Constructor for class org.deeplearning4j.models.sequencevectors.transformers.impl.iterables.ParallelTransformerIterator
-
- ParallelWrapper - Class in org.deeplearning4j.parallelism
-
This is simple data-parallel wrapper
suitable for multi-cpu/multi-gpu environments.
- ParallelWrapper(Model, int, int) - Constructor for class org.deeplearning4j.parallelism.ParallelWrapper
-
- parallelWrapper(ParallelWrapper) - Method in class org.deeplearning4j.parallelism.parameterserver.ParameterServerTrainer.ParameterServerTrainerBuilder
-
- parallelWrapper - Variable in class org.deeplearning4j.parallelism.trainer.DefaultTrainer
-
- ParallelWrapper.Builder<T extends Model> - Class in org.deeplearning4j.parallelism
-
- ParallelWrapper.TrainingMode - Enum in org.deeplearning4j.parallelism
-
- ParallelWrapperMain - Class in org.deeplearning4j.parallelism.main
-
Parallelwrapper main class.
- ParallelWrapperMain() - Constructor for class org.deeplearning4j.parallelism.main.ParallelWrapperMain
-
- param - Variable in class org.ansj.domain.AnsjItem
-
- ParamAndGradientIterationListener - Class in org.deeplearning4j.optimize.listeners
-
An iteration listener that provides details on parameters and gradients at each iteration during traning.
- ParamAndGradientIterationListener() - Constructor for class org.deeplearning4j.optimize.listeners.ParamAndGradientIterationListener
-
Default constructor for output to console only every iteration, tab delimited
- ParamAndGradientIterationListener(int, boolean, boolean, boolean, boolean, boolean, boolean, boolean, File, String) - Constructor for class org.deeplearning4j.optimize.listeners.ParamAndGradientIterationListener
-
Full constructor with all options.
- PARAMETER_AVERAGING_MASTER_AGGREGATE_TIMES_MS - Static variable in class org.deeplearning4j.spark.impl.paramavg.stats.ParameterAveragingTrainingMasterStats
-
- PARAMETER_AVERAGING_MASTER_BROADCAST_CREATE_TIMES_MS - Static variable in class org.deeplearning4j.spark.impl.paramavg.stats.ParameterAveragingTrainingMasterStats
-
- PARAMETER_AVERAGING_MASTER_COUNT_RDD_TIMES_MS - Static variable in class org.deeplearning4j.spark.impl.paramavg.stats.ParameterAveragingTrainingMasterStats
-
- PARAMETER_AVERAGING_MASTER_EXPORT_RDD_TIMES_MS - Static variable in class org.deeplearning4j.spark.impl.paramavg.stats.ParameterAveragingTrainingMasterStats
-
- PARAMETER_AVERAGING_MASTER_FIT_TIMES_MS - Static variable in class org.deeplearning4j.spark.impl.paramavg.stats.ParameterAveragingTrainingMasterStats
-
- PARAMETER_AVERAGING_MASTER_MAP_PARTITIONS_TIMES_MS - Static variable in class org.deeplearning4j.spark.impl.paramavg.stats.ParameterAveragingTrainingMasterStats
-
- PARAMETER_AVERAGING_MASTER_PROCESS_PARAMS_UPDATER_TIMES_MS - Static variable in class org.deeplearning4j.spark.impl.paramavg.stats.ParameterAveragingTrainingMasterStats
-
- PARAMETER_AVERAGING_MASTER_REPARTITION_TIMES_MS - Static variable in class org.deeplearning4j.spark.impl.paramavg.stats.ParameterAveragingTrainingMasterStats
-
- PARAMETER_AVERAGING_MASTER_SPLIT_TIMES_MS - Static variable in class org.deeplearning4j.spark.impl.paramavg.stats.ParameterAveragingTrainingMasterStats
-
- PARAMETER_AVERAGING_WORKER_BROADCAST_GET_VALUE_TIME_MS - Static variable in class org.deeplearning4j.spark.impl.paramavg.stats.ParameterAveragingTrainingWorkerStats
-
- PARAMETER_AVERAGING_WORKER_FIT_TIMES_MS - Static variable in class org.deeplearning4j.spark.impl.paramavg.stats.ParameterAveragingTrainingWorkerStats
-
- PARAMETER_AVERAGING_WORKER_INIT_TIME_MS - Static variable in class org.deeplearning4j.spark.impl.paramavg.stats.ParameterAveragingTrainingWorkerStats
-
- ParameterAveragingAggregationTuple - Class in org.deeplearning4j.spark.impl.paramavg.aggregator
-
Simple helper tuple used to execute parameter averaging
- ParameterAveragingAggregationTuple() - Constructor for class org.deeplearning4j.spark.impl.paramavg.aggregator.ParameterAveragingAggregationTuple
-
- ParameterAveragingElementAddFunction - Class in org.deeplearning4j.spark.impl.paramavg.aggregator
-
Add function for parameter averaging
- ParameterAveragingElementAddFunction() - Constructor for class org.deeplearning4j.spark.impl.paramavg.aggregator.ParameterAveragingElementAddFunction
-
- ParameterAveragingElementCombineFunction - Class in org.deeplearning4j.spark.impl.paramavg.aggregator
-
Function used in ParameterAveraging TrainingMaster, for doing parameter averaging, and handling updaters
- ParameterAveragingElementCombineFunction() - Constructor for class org.deeplearning4j.spark.impl.paramavg.aggregator.ParameterAveragingElementCombineFunction
-
- ParameterAveragingTrainingMaster - Class in org.deeplearning4j.spark.impl.paramavg
-
ParameterAveragingTrainingMaster: A
TrainingMaster
implementation for training networks on Spark.
- ParameterAveragingTrainingMaster() - Constructor for class org.deeplearning4j.spark.impl.paramavg.ParameterAveragingTrainingMaster
-
- ParameterAveragingTrainingMaster(ParameterAveragingTrainingMaster.Builder) - Constructor for class org.deeplearning4j.spark.impl.paramavg.ParameterAveragingTrainingMaster
-
- ParameterAveragingTrainingMaster(boolean, Integer, int, int, int, int) - Constructor for class org.deeplearning4j.spark.impl.paramavg.ParameterAveragingTrainingMaster
-
- ParameterAveragingTrainingMaster(boolean, Integer, int, int, int, int, int, Repartition, RepartitionStrategy, boolean) - Constructor for class org.deeplearning4j.spark.impl.paramavg.ParameterAveragingTrainingMaster
-
- ParameterAveragingTrainingMaster(boolean, Integer, int, int, int, int, int, Repartition, RepartitionStrategy, StorageLevel, boolean) - Constructor for class org.deeplearning4j.spark.impl.paramavg.ParameterAveragingTrainingMaster
-
- ParameterAveragingTrainingMaster.Builder - Class in org.deeplearning4j.spark.impl.paramavg
-
- ParameterAveragingTrainingMasterStats - Class in org.deeplearning4j.spark.impl.paramavg.stats
-
- ParameterAveragingTrainingMasterStats(SparkTrainingStats, List<EventStats>, List<EventStats>, List<EventStats>, List<EventStats>, List<EventStats>, List<EventStats>, List<EventStats>, List<EventStats>, List<EventStats>) - Constructor for class org.deeplearning4j.spark.impl.paramavg.stats.ParameterAveragingTrainingMasterStats
-
- ParameterAveragingTrainingMasterStats.ParameterAveragingTrainingMasterStatsHelper - Class in org.deeplearning4j.spark.impl.paramavg.stats
-
- ParameterAveragingTrainingMasterStatsHelper() - Constructor for class org.deeplearning4j.spark.impl.paramavg.stats.ParameterAveragingTrainingMasterStats.ParameterAveragingTrainingMasterStatsHelper
-
- ParameterAveragingTrainingResult - Class in org.deeplearning4j.spark.impl.paramavg
-
- ParameterAveragingTrainingResult(INDArray, INDArray, double, Collection<StorageMetaData>, Collection<Persistable>, Collection<Persistable>) - Constructor for class org.deeplearning4j.spark.impl.paramavg.ParameterAveragingTrainingResult
-
- ParameterAveragingTrainingResult(INDArray, INDArray, double, SparkTrainingStats, Collection<StorageMetaData>, Collection<Persistable>, Collection<Persistable>) - Constructor for class org.deeplearning4j.spark.impl.paramavg.ParameterAveragingTrainingResult
-
- ParameterAveragingTrainingWorker - Class in org.deeplearning4j.spark.impl.paramavg
-
ParameterAveragingTrainingWorker
implements standard parameter
averaging every m iterations.
- ParameterAveragingTrainingWorker(Broadcast<NetBroadcastTuple>, boolean, WorkerConfiguration, Collection<TrainingHook>, Collection<TrainingListener>, StatsStorageRouterProvider) - Constructor for class org.deeplearning4j.spark.impl.paramavg.ParameterAveragingTrainingWorker
-
- ParameterAveragingTrainingWorkerStats - Class in org.deeplearning4j.spark.impl.paramavg.stats
-
- ParameterAveragingTrainingWorkerStats(List<EventStats>, List<EventStats>, List<EventStats>) - Constructor for class org.deeplearning4j.spark.impl.paramavg.stats.ParameterAveragingTrainingWorkerStats
-
- ParameterAveragingTrainingWorkerStats.ParameterAveragingTrainingWorkerStatsHelper - Class in org.deeplearning4j.spark.impl.paramavg.stats
-
- ParameterAveragingTrainingWorkerStatsHelper() - Constructor for class org.deeplearning4j.spark.impl.paramavg.stats.ParameterAveragingTrainingWorkerStats.ParameterAveragingTrainingWorkerStatsHelper
-
- ParameterServerSubscriber - Class in org.deeplearning4j.spark.parameterserver
-
Created by agibsonccc on 9/27/16.
- ParameterServerSubscriber() - Constructor for class org.deeplearning4j.spark.parameterserver.ParameterServerSubscriber
-
- ParameterServerTrainer - Class in org.deeplearning4j.parallelism.parameterserver
-
Using an ParameterServerClient
we maintain updates for training a neural net.
- ParameterServerTrainer() - Constructor for class org.deeplearning4j.parallelism.parameterserver.ParameterServerTrainer
-
- ParameterServerTrainer.ParameterServerTrainerBuilder - Class in org.deeplearning4j.parallelism.parameterserver
-
- ParameterServerTrainerBuilder() - Constructor for class org.deeplearning4j.parallelism.parameterserver.ParameterServerTrainer.ParameterServerTrainerBuilder
-
- ParameterServerTrainerContext - Class in org.deeplearning4j.parallelism.parameterserver
-
- ParameterServerTrainerContext() - Constructor for class org.deeplearning4j.parallelism.parameterserver.ParameterServerTrainerContext
-
- ParameterServerTrainingHook - Class in org.deeplearning4j.spark.parameterserver
-
Training hook for the
parameter server
- ParameterServerTrainingHook() - Constructor for class org.deeplearning4j.spark.parameterserver.ParameterServerTrainingHook
-
- ParamInitializer - Interface in org.deeplearning4j.nn.api
-
Param initializer for a layer
- paramKeys(Layer) - Method in interface org.deeplearning4j.nn.api.ParamInitializer
-
Get a list of all parameter keys given the layer configuration
- paramKeys(Layer) - Method in class org.deeplearning4j.nn.layers.ocnn.OCNNParamInitializer
-
- paramKeys(Layer) - Method in class org.deeplearning4j.nn.params.BatchNormalizationParamInitializer
-
- paramKeys(Layer) - Method in class org.deeplearning4j.nn.params.BidirectionalParamInitializer
-
- paramKeys(Layer) - Method in class org.deeplearning4j.nn.params.ConvolutionParamInitializer
-
- paramKeys(Layer) - Method in class org.deeplearning4j.nn.params.DefaultParamInitializer
-
- paramKeys(Layer) - Method in class org.deeplearning4j.nn.params.DepthwiseConvolutionParamInitializer
-
- paramKeys(Layer) - Method in class org.deeplearning4j.nn.params.EmptyParamInitializer
-
- paramKeys(Layer) - Method in class org.deeplearning4j.nn.params.FrozenLayerParamInitializer
-
- paramKeys(Layer) - Method in class org.deeplearning4j.nn.params.FrozenLayerWithBackpropParamInitializer
-
- paramKeys(Layer) - Method in class org.deeplearning4j.nn.params.GravesBidirectionalLSTMParamInitializer
-
- paramKeys(Layer) - Method in class org.deeplearning4j.nn.params.GravesLSTMParamInitializer
-
- paramKeys(Layer) - Method in class org.deeplearning4j.nn.params.LSTMParamInitializer
-
- paramKeys(Layer) - Method in class org.deeplearning4j.nn.params.SameDiffParamInitializer
-
- paramKeys(Layer) - Method in class org.deeplearning4j.nn.params.SeparableConvolutionParamInitializer
-
- paramKeys(Layer) - Method in class org.deeplearning4j.nn.params.SimpleRnnParamInitializer
-
- paramKeys(Layer) - Method in class org.deeplearning4j.nn.params.VariationalAutoencoderParamInitializer
-
- paramKeys(Layer) - Method in class org.deeplearning4j.nn.params.WrapperLayerParamInitializer
-
- paramName() - Method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder.ParamNamesDecoder
-
- paramName(String) - Method in class org.deeplearning4j.ui.stats.sbe.UpdateEncoder.ParamNamesEncoder
-
- paramNameCharacterEncoding() - Static method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder.ParamNamesDecoder
-
- paramNameCharacterEncoding() - Static method in class org.deeplearning4j.ui.stats.sbe.UpdateEncoder.ParamNamesEncoder
-
- paramNameHeaderLength() - Static method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder.ParamNamesDecoder
-
- paramNameHeaderLength() - Static method in class org.deeplearning4j.ui.stats.sbe.UpdateEncoder.ParamNamesEncoder
-
- paramNameId() - Static method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder.ParamNamesDecoder
-
- paramNameId() - Static method in class org.deeplearning4j.ui.stats.sbe.UpdateEncoder.ParamNamesEncoder
-
- paramNameLength() - Method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder.ParamNamesDecoder
-
- paramNameMetaAttribute(MetaAttribute) - Static method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder.ParamNamesDecoder
-
- paramNameMetaAttribute(MetaAttribute) - Static method in class org.deeplearning4j.ui.stats.sbe.UpdateEncoder.ParamNamesEncoder
-
- paramNames() - Method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder
-
- paramNamesCount(int) - Method in class org.deeplearning4j.ui.stats.sbe.UpdateEncoder
-
- ParamNamesDecoder() - Constructor for class org.deeplearning4j.ui.stats.sbe.UpdateDecoder.ParamNamesDecoder
-
- paramNamesDecoderId() - Static method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder
-
- ParamNamesEncoder() - Constructor for class org.deeplearning4j.ui.stats.sbe.UpdateEncoder.ParamNamesEncoder
-
- paramNamesId() - Static method in class org.deeplearning4j.ui.stats.sbe.UpdateEncoder
-
- paramReshapeOrder(String) - Method in class org.deeplearning4j.nn.conf.layers.samediff.AbstractSameDiffLayer
-
Returns the memory layout ('c' or 'f' order - i.e., row/column major) of the parameters.
- params() - Method in interface org.deeplearning4j.nn.api.Model
-
Parameters of the model (if any)
- params() - Method in interface org.deeplearning4j.nn.api.NeuralNetwork
-
This method returns model parameters as single INDArray
- params - Variable in class org.deeplearning4j.nn.conf.constraint.BaseConstraint
-
- params(boolean) - Method in class org.deeplearning4j.nn.graph.ComputationGraph
-
Get the parameters for the ComputationGraph
- params() - Method in class org.deeplearning4j.nn.graph.ComputationGraph
-
- params() - Method in class org.deeplearning4j.nn.layers.AbstractLayer
-
Returns the parameters of the neural network as a flattened row vector
- params() - Method in class org.deeplearning4j.nn.layers.ActivationLayer
-
- params - Variable in class org.deeplearning4j.nn.layers.BaseLayer
-
- params() - Method in class org.deeplearning4j.nn.layers.BaseLayer
-
Returns the parameters of the neural network as a flattened row vector
- params() - Method in class org.deeplearning4j.nn.layers.BasePretrainNetwork
-
- params() - Method in class org.deeplearning4j.nn.layers.convolution.ConvolutionLayer
-
- params() - Method in class org.deeplearning4j.nn.layers.convolution.SpaceToBatch
-
- params() - Method in class org.deeplearning4j.nn.layers.convolution.SpaceToDepth
-
- params() - Method in class org.deeplearning4j.nn.layers.convolution.subsampling.Subsampling3DLayer
-
- params() - Method in class org.deeplearning4j.nn.layers.convolution.subsampling.SubsamplingLayer
-
- params() - Method in class org.deeplearning4j.nn.layers.convolution.upsampling.Upsampling2D
-
- params() - Method in class org.deeplearning4j.nn.layers.convolution.upsampling.Upsampling3D
-
- params() - Method in class org.deeplearning4j.nn.layers.DropoutLayer
-
- params() - Method in class org.deeplearning4j.nn.layers.LossLayer
-
- params() - Method in class org.deeplearning4j.nn.layers.normalization.LocalResponseNormalization
-
- params() - Method in class org.deeplearning4j.nn.layers.recurrent.BidirectionalLayer
-
- params - Variable in class org.deeplearning4j.nn.layers.samediff.SameDiffLayer
-
- params() - Method in class org.deeplearning4j.nn.layers.samediff.SameDiffLayer
-
Returns the parameters of the neural network as a flattened row vector
- params - Variable in class org.deeplearning4j.nn.layers.variational.VariationalAutoencoder
-
- params() - Method in class org.deeplearning4j.nn.layers.variational.VariationalAutoencoder
-
- params() - Method in class org.deeplearning4j.nn.layers.wrapper.BaseWrapperLayer
-
- params(boolean) - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
-
Returns a 1 x m vector where the vector is composed of
a flattened vector of all of the weights for the
various neuralNets(w,hbias NOT VBIAS) and output layer
- params() - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
-
Returns a 1 x m vector where the vector is composed of
a flattened vector of all of the weights for the
various neuralNets(w,hbias NOT VBIAS) and output layer
- params() - Method in class org.deeplearning4j.plot.BarnesHutTsne
-
- params - Variable in class org.deeplearning4j.spark.impl.common.score.BaseVaeScoreWithKeyFunctionAdapter
-
- params - Variable in class org.deeplearning4j.spark.parameterserver.networking.SilentTrainingDriver
-
- PARAMS_KEY - Static variable in class org.deeplearning4j.optimize.solvers.BaseOptimizer
-
- paramServer - Variable in class org.deeplearning4j.spark.models.sequencevectors.functions.PartitionTrainingFunction
-
- paramServer - Variable in class org.deeplearning4j.spark.models.sequencevectors.functions.TrainingFunction
-
- paramServerConfiguration - Variable in class org.deeplearning4j.spark.models.sequencevectors.SparkSequenceVectors
-
- paramServerConfigurationBroadcast - Variable in class org.deeplearning4j.spark.models.sequencevectors.functions.PartitionTrainingFunction
-
- paramServerConfigurationBroadcast - Variable in class org.deeplearning4j.spark.models.sequencevectors.functions.TrainingFunction
-
- paramsFlattened - Variable in class org.deeplearning4j.nn.layers.BaseLayer
-
- paramsFlattened - Variable in class org.deeplearning4j.nn.layers.variational.VariationalAutoencoder
-
- ParamState() - Constructor for class org.deeplearning4j.nn.updater.UpdaterBlock.ParamState
-
- paramTable() - Method in interface org.deeplearning4j.nn.api.Model
-
The param table
- paramTable(boolean) - Method in interface org.deeplearning4j.nn.api.Model
-
Table of parameters by key, for backprop
For many models (dense layers, etc) - all parameters are backprop parameters
- paramTable() - Method in class org.deeplearning4j.nn.graph.ComputationGraph
-
- paramTable(boolean) - Method in class org.deeplearning4j.nn.graph.ComputationGraph
-
- paramTable() - Method in class org.deeplearning4j.nn.layers.AbstractLayer
-
- paramTable(boolean) - Method in class org.deeplearning4j.nn.layers.AbstractLayer
-
- paramTable() - Method in class org.deeplearning4j.nn.layers.BaseLayer
-
- paramTable(boolean) - Method in class org.deeplearning4j.nn.layers.BaseLayer
-
- paramTable(boolean) - Method in class org.deeplearning4j.nn.layers.BasePretrainNetwork
-
- paramTable() - Method in class org.deeplearning4j.nn.layers.recurrent.BidirectionalLayer
-
- paramTable(boolean) - Method in class org.deeplearning4j.nn.layers.recurrent.BidirectionalLayer
-
- paramTable - Variable in class org.deeplearning4j.nn.layers.samediff.SameDiffLayer
-
- paramTable() - Method in class org.deeplearning4j.nn.layers.samediff.SameDiffLayer
-
- paramTable(boolean) - Method in class org.deeplearning4j.nn.layers.samediff.SameDiffLayer
-
- paramTable() - Method in class org.deeplearning4j.nn.layers.variational.VariationalAutoencoder
-
- paramTable(boolean) - Method in class org.deeplearning4j.nn.layers.variational.VariationalAutoencoder
-
- paramTable() - Method in class org.deeplearning4j.nn.layers.wrapper.BaseWrapperLayer
-
- paramTable(boolean) - Method in class org.deeplearning4j.nn.layers.wrapper.BaseWrapperLayer
-
- paramTable() - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
-
- paramTable(boolean) - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
-
- paramTable() - Method in class org.deeplearning4j.plot.BarnesHutTsne
-
- paramTable(boolean) - Method in class org.deeplearning4j.plot.BarnesHutTsne
-
- parent(Tree) - Method in class org.deeplearning4j.nn.layers.feedforward.autoencoder.recursive.Tree
-
Returns the parent of the passed in tree via traversal
- parent() - Method in class org.deeplearning4j.nn.layers.feedforward.autoencoder.recursive.Tree
-
- parse(String) - Method in class com.atilika.kuromoji.compile.TokenInfoDictionaryCompilerBase
-
- parse(String) - Method in class com.atilika.kuromoji.ipadic.compile.TokenInfoDictionaryCompiler
-
- parse(String) - Method in class com.atilika.kuromoji.util.UnknownDictionaryEntryParser
-
- parse(String) - Static method in class org.ansj.splitWord.analysis.BaseAnalysis
-
- parse(String) - Static method in class org.ansj.splitWord.analysis.DicAnalysis
-
- parse(String, Forest...) - Static method in class org.ansj.splitWord.analysis.DicAnalysis
-
- parse(String) - Static method in class org.ansj.splitWord.analysis.IndexAnalysis
-
- parse(String, Forest...) - Static method in class org.ansj.splitWord.analysis.IndexAnalysis
-
- parse(String) - Static method in class org.ansj.splitWord.analysis.NlpAnalysis
-
- parse(String, Forest...) - Static method in class org.ansj.splitWord.analysis.NlpAnalysis
-
- parse() - Method in class org.ansj.splitWord.Analysis
-
通过构造方法传入的reader直接获取到分词结果
- parse(String) - Static method in class org.ansj.splitWord.analysis.ToAnalysis
-
- parse(String, Forest...) - Static method in class org.ansj.splitWord.analysis.ToAnalysis
-
- ParseException - Exception in org.deeplearning4j.graph.exception
-
Unchecked exception signifying that an error occurred during parsing of text
- ParseException() - Constructor for exception org.deeplearning4j.graph.exception.ParseException
-
- ParseException(String) - Constructor for exception org.deeplearning4j.graph.exception.ParseException
-
- ParseException(String, Exception) - Constructor for exception org.deeplearning4j.graph.exception.ParseException
-
- ParseException - Exception in org.deeplearning4j.models.sequencevectors.graph.exception
-
Unchecked exception signifying that an error occurred during parsing of text
- ParseException() - Constructor for exception org.deeplearning4j.models.sequencevectors.graph.exception.ParseException
-
- ParseException(String) - Constructor for exception org.deeplearning4j.models.sequencevectors.graph.exception.ParseException
-
- ParseException(String, Exception) - Constructor for exception org.deeplearning4j.models.sequencevectors.graph.exception.ParseException
-
- parseJsonString(String) - Static method in class org.deeplearning4j.nn.modelimport.keras.utils.KerasModelUtils
-
Convenience function for parsing JSON strings.
- parseLine(String) - Static method in class com.atilika.kuromoji.util.DictionaryEntryLineParser
-
Parse CSV line
- parseModelConfig(String, String) - Static method in class org.deeplearning4j.nn.modelimport.keras.utils.KerasModelUtils
-
Parse Keras model configuration from JSON or YAML string representation
- parseNature(Term) - Static method in class org.ansj.util.TermUtil
-
得到细颗粒度的分词，并且确定词性
- parseStr(String) - Method in class org.ansj.splitWord.Analysis
-
一句话进行分词并且封装
- parseYamlString(String) - Static method in class org.deeplearning4j.nn.modelimport.keras.utils.KerasModelUtils
-
Convenience function for parsing YAML strings.
- PART_OF_SPEECH_FEATURE - Static variable in class com.atilika.kuromoji.ipadic.compile.DictionaryEntry
-
- PART_OF_SPEECH_LEVEL_1 - Static variable in class com.atilika.kuromoji.ipadic.compile.DictionaryEntry
-
- PART_OF_SPEECH_LEVEL_2 - Static variable in class com.atilika.kuromoji.ipadic.compile.DictionaryEntry
-
- PART_OF_SPEECH_LEVEL_3 - Static variable in class com.atilika.kuromoji.ipadic.compile.DictionaryEntry
-
- PART_OF_SPEECH_LEVEL_4 - Static variable in class com.atilika.kuromoji.ipadic.compile.DictionaryEntry
-
- parties - Variable in class org.deeplearning4j.optimize.solvers.accumulation.BasicGradientsAccumulator
-
- parties - Variable in class org.deeplearning4j.optimize.solvers.accumulation.EncodedGradientsAccumulator.Builder
-
- parties - Variable in class org.deeplearning4j.optimize.solvers.accumulation.EncodedGradientsAccumulator
-
- PartitionCountEventStats - Class in org.deeplearning4j.spark.stats
-
Event stats implementation with partition count
- PartitionCountEventStats(long, long, int) - Constructor for class org.deeplearning4j.spark.stats.PartitionCountEventStats
-
- PartitionCountEventStats(String, String, long, long, long, int) - Constructor for class org.deeplearning4j.spark.stats.PartitionCountEventStats
-
- PartitionTrainingFunction<T extends SequenceElement> - Class in org.deeplearning4j.spark.models.sequencevectors.functions
-
- PartitionTrainingFunction(Broadcast<VocabCache<ShallowSequenceElement>>, Broadcast<VectorsConfiguration>, Broadcast<VoidConfiguration>) - Constructor for class org.deeplearning4j.spark.models.sequencevectors.functions.PartitionTrainingFunction
-
- partitionVariable(List<Double>, int) - Static method in class org.deeplearning4j.clustering.util.MathUtils
-
- partOfSpeechFeature - Variable in class com.atilika.kuromoji.TokenizerBase.Builder
-
- passDataSet(DataSet) - Method in class org.deeplearning4j.spark.parameterserver.pw.SharedTrainingWrapper
-
- passDataSet(MultiDataSet) - Method in class org.deeplearning4j.spark.parameterserver.pw.SharedTrainingWrapper
-
- path - Variable in class org.deeplearning4j.spark.models.sequencevectors.export.impl.HdfsModelExporter
-
- path - Variable in class org.deeplearning4j.text.sentenceiterator.UimaSentenceIterator
-
- PathSparkDataSetIterator - Class in org.deeplearning4j.spark.iterator
-
A DataSetIterator that loads serialized DataSet objects (saved with DataSet.save(OutputStream)) from
a String that represents the path (for example, on HDFS)
- PathSparkDataSetIterator(Iterator<String>) - Constructor for class org.deeplearning4j.spark.iterator.PathSparkDataSetIterator
-
- PathSparkDataSetIterator(Collection<String>) - Constructor for class org.deeplearning4j.spark.iterator.PathSparkDataSetIterator
-
- PathSparkMultiDataSetIterator - Class in org.deeplearning4j.spark.iterator
-
A DataSetIterator that loads serialized DataSet objects (saved with MultiDataSet.save(OutputStream)) from
a String that represents the path (for example, on HDFS)
- PathSparkMultiDataSetIterator(Iterator<String>) - Constructor for class org.deeplearning4j.spark.iterator.PathSparkMultiDataSetIterator
-
- PathSparkMultiDataSetIterator(Collection<String>) - Constructor for class org.deeplearning4j.spark.iterator.PathSparkMultiDataSetIterator
-
- PathToDataSetFunction - Class in org.deeplearning4j.spark.data
-
Simple function used to load DataSets (serialized with DataSet.save()) from a given Path (as a String)
to a DataSet object - i.e., RDD<String> to RDD<DataSet>
- PathToDataSetFunction() - Constructor for class org.deeplearning4j.spark.data.PathToDataSetFunction
-
- PathToMultiDataSetFunction - Class in org.deeplearning4j.spark.data
-
Simple function used to load MultiDataSets (serialized with MultiDataSet.save()) from a given Path (as a String)
to a MultiDataSet object - i.e., RDD<String> to RDD<MultiDataSet>
- PathToMultiDataSetFunction() - Constructor for class org.deeplearning4j.spark.data.PathToMultiDataSetFunction
-
- PathToStream - Class in org.ansj.dic
-
将路径转换为流，如果你需要实现自己的加载器请实现这个类，使用这个类可能需要自己依赖第三方包，比如jdbc连接和nutz
- PathToStream() - Constructor for class org.ansj.dic.PathToStream
-
- PathUpdate - Class in org.deeplearning4j.ui.activation
-
- PathUpdate() - Constructor for class org.deeplearning4j.ui.activation.PathUpdate
-
- PathUpdate - Class in org.deeplearning4j.ui.renders
-
- PathUpdate() - Constructor for class org.deeplearning4j.ui.renders.PathUpdate
-
- PatriciaNode(String, V, int) - Constructor for class com.atilika.kuromoji.trie.PatriciaTrie.PatriciaNode
-
Constructs a new node
- PatriciaTrie<V> - Class in com.atilika.kuromoji.trie
-
Convenient and compact structure for storing key-value pairs and quickly
looking them up, including doing prefix searches
- PatriciaTrie() - Constructor for class com.atilika.kuromoji.trie.PatriciaTrie
-
Constructs and empty trie
- PatriciaTrie.KeyMapper<K> - Interface in com.atilika.kuromoji.trie
-
Generic interface to map a key to bits
- PatriciaTrie.PatriciaNode<V> - Class in com.atilika.kuromoji.trie
-
Nodes used in a
PatriciaTrie containing a String key and associated value data
- PatriciaTrie.StringKeyMapper - Class in com.atilika.kuromoji.trie
-
- PatriciaTrieFormatter<V> - Class in com.atilika.kuromoji.trie
-
Utility class to format a
PatriciaTrie to dot format for debugging, inspection, etc.
- PatriciaTrieFormatter() - Constructor for class com.atilika.kuromoji.trie.PatriciaTrieFormatter
-
Constructor
- pattern0 - Static variable in class org.deeplearning4j.spark.models.sequencevectors.export.ExportContainer
-
- pattern1 - Static variable in class org.deeplearning4j.spark.models.sequencevectors.export.ExportContainer
-
- PdsIterator - Class in org.deeplearning4j.spark.parameterserver.iterators
-
- PdsIterator(Iterator<PortableDataStream>, PortableDataStreamCallback) - Constructor for class org.deeplearning4j.spark.parameterserver.iterators.PdsIterator
-
- pearsonCorrelation(int) - Method in class org.deeplearning4j.eval.RegressionEvaluation
-
Pearson Correlation Coefficient for samples
- peek() - Method in class org.deeplearning4j.optimize.solvers.accumulation.FancyBlockingQueue
-
- peek() - Method in class org.deeplearning4j.parallelism.MagicQueue
-
Deprecated.
- peek() - Method in class org.deeplearning4j.util.DiskBasedQueue
-
- peersConfiguration - Variable in class org.deeplearning4j.spark.models.sequencevectors.SparkSequenceVectors.Builder
-
- penalties - Variable in class com.atilika.kuromoji.TokenizerBase.Builder
-
- performance() - Method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder
-
- performance() - Method in class org.deeplearning4j.ui.stats.sbe.UpdateFieldsPresentDecoder
-
- performance(boolean) - Method in class org.deeplearning4j.ui.stats.sbe.UpdateFieldsPresentEncoder
-
- performanceCount(int) - Method in class org.deeplearning4j.ui.stats.sbe.UpdateEncoder
-
- PerformanceDecoder() - Constructor for class org.deeplearning4j.ui.stats.sbe.UpdateDecoder.PerformanceDecoder
-
- performanceDecoderId() - Static method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder
-
- PerformanceEncoder() - Constructor for class org.deeplearning4j.ui.stats.sbe.UpdateEncoder.PerformanceEncoder
-
- performanceId() - Static method in class org.deeplearning4j.ui.stats.sbe.UpdateEncoder
-
- PerformanceListener - Class in org.deeplearning4j.optimize.listeners
-
Simple IterationListener that tracks time spend on training per iteration.
- PerformanceListener(int) - Constructor for class org.deeplearning4j.optimize.listeners.PerformanceListener
-
- PerformanceListener(int, boolean) - Constructor for class org.deeplearning4j.optimize.listeners.PerformanceListener
-
- PerformanceListener.Builder - Class in org.deeplearning4j.optimize.listeners
-
- permutation(double, double) - Static method in class org.deeplearning4j.clustering.util.MathUtils
-
This returns the permutation of n choose r.
- PermutePreprocessor - Class in org.deeplearning4j.nn.modelimport.keras.preprocessors
-
Preprocessor to permute input data according to specified permutation indices.
- PermutePreprocessor(int[]) - Constructor for class org.deeplearning4j.nn.modelimport.keras.preprocessors.PermutePreprocessor
-
- perParameterStats() - Method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder
-
- perParameterStatsCount(int) - Method in class org.deeplearning4j.ui.stats.sbe.UpdateEncoder
-
- PerParameterStatsDecoder() - Constructor for class org.deeplearning4j.ui.stats.sbe.UpdateDecoder.PerParameterStatsDecoder
-
- perParameterStatsDecoderId() - Static method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder
-
- PerParameterStatsEncoder() - Constructor for class org.deeplearning4j.ui.stats.sbe.UpdateEncoder.PerParameterStatsEncoder
-
- perParameterStatsId() - Static method in class org.deeplearning4j.ui.stats.sbe.UpdateEncoder
-
- perplexity(double) - Method in class org.deeplearning4j.plot.BarnesHutTsne.Builder
-
- perplexity - Variable in class org.deeplearning4j.plot.BarnesHutTsne
-
- perplexity - Variable in class org.deeplearning4j.plot.Tsne.Builder
-
- perplexity(double) - Method in class org.deeplearning4j.plot.Tsne.Builder
-
- perplexity - Variable in class org.deeplearning4j.plot.Tsne
-
- Persistable - Interface in org.deeplearning4j.api.storage
-
Created by Alex on 07/10/2016.
- personAttr - Variable in class org.ansj.domain.TermNatures
-
人名词性
- PersonAttrLibrary - Class in org.ansj.library.name
-
人名标注所用的词典就是简单的hashmap简单方便谁用谁知道,只在加载词典的时候用
- PersonAttrLibrary() - Constructor for class org.ansj.library.name.PersonAttrLibrary
-
- PersonNatureAttr - Class in org.ansj.domain
-
人名标注pojo类
- PersonNatureAttr() - Constructor for class org.ansj.domain.PersonNatureAttr
-
- pickTraining(SilentUpdatesMessage) - Method in class org.deeplearning4j.spark.parameterserver.networking.SilentTrainingDriver
-
- Pipeline - Interface in org.deeplearning4j
-
A pipeline consists of a
set of input,output, and datavec uris.
- PlayUIServer - Class in org.deeplearning4j.ui.play
-
A UI server based on the Play framework
- PlayUIServer() - Constructor for class org.deeplearning4j.ui.play.PlayUIServer
-
- PlayUIServer(int) - Constructor for class org.deeplearning4j.ui.play.PlayUIServer
-
- plot(INDArray, int, List<String>, String) - Method in class org.deeplearning4j.plot.BarnesHutTsne
-
- plot(INDArray, int, List<String>, String) - Method in class org.deeplearning4j.plot.Tsne
-
- plotVocab(BarnesHutTsne, int, File) - Method in class org.deeplearning4j.models.embeddings.inmemory.InMemoryLookupTable
-
- plotVocab(int, File) - Method in class org.deeplearning4j.models.embeddings.inmemory.InMemoryLookupTable
-
Render the words via tsne
- plotVocab(int, UiConnectionInfo) - Method in class org.deeplearning4j.models.embeddings.inmemory.InMemoryLookupTable
-
Render the words via tsne
- plotVocab(BarnesHutTsne, int, UiConnectionInfo) - Method in class org.deeplearning4j.models.embeddings.inmemory.InMemoryLookupTable
-
Render the words via TSNE
- plotVocab(BarnesHutTsne, int, UiConnectionInfo) - Method in interface org.deeplearning4j.models.embeddings.WeightLookupTable
-
Render the words via TSNE
- plotVocab(BarnesHutTsne, int, File) - Method in interface org.deeplearning4j.models.embeddings.WeightLookupTable
-
Render the words via TSNE
- plotVocab(int, UiConnectionInfo) - Method in interface org.deeplearning4j.models.embeddings.WeightLookupTable
-
Render the words via tsne
- plotVocab(int, File) - Method in interface org.deeplearning4j.models.embeddings.WeightLookupTable
-
Render the words via tsne
- pnorm(int) - Method in class org.deeplearning4j.nn.conf.layers.GlobalPoolingLayer.Builder
-
P-norm constant.
- pnorm - Variable in class org.deeplearning4j.nn.conf.layers.SubsamplingLayer.BaseSubsamplingBuilder
-
- pnorm(int) - Method in class org.deeplearning4j.nn.conf.layers.SubsamplingLayer.BaseSubsamplingBuilder
-
- pnorm - Variable in class org.deeplearning4j.nn.conf.layers.SubsamplingLayer
-
- pNormNxN(int, int, int) - Static method in class org.deeplearning4j.zoo.model.helper.FaceNetHelper
-
- Point - Class in org.deeplearning4j.clustering.cluster
-
- Point(INDArray) - Constructor for class org.deeplearning4j.clustering.cluster.Point
-
- Point(String, INDArray) - Constructor for class org.deeplearning4j.clustering.cluster.Point
-
- Point(String, String, double[]) - Constructor for class org.deeplearning4j.clustering.cluster.Point
-
- Point(String, String, INDArray) - Constructor for class org.deeplearning4j.clustering.cluster.Point
-
- point(INDArray) - Static method in class org.deeplearning4j.clustering.kdtree.HyperRect
-
- Point() - Constructor for class org.deeplearning4j.eval.curves.PrecisionRecallCurve.Point
-
- POINT_WISE_WEIGHT_KEY - Static variable in class org.deeplearning4j.nn.params.SeparableConvolutionParamInitializer
-
- PointClassification - Class in org.deeplearning4j.clustering.cluster
-
- PointClassification() - Constructor for class org.deeplearning4j.clustering.cluster.PointClassification
-
- pointOf(Collection<Writable>) - Static method in class org.deeplearning4j.spark.util.MLLibUtil
-
Returns a labeled point of the writables
where the final item is the point and the rest of the items are
features
- points - Variable in class org.deeplearning4j.models.sequencevectors.sequence.SequenceElement
-
- pointSize - Variable in class org.deeplearning4j.ui.components.chart.style.StyleChart.Builder
-
- pointSize(double) - Method in class org.deeplearning4j.ui.components.chart.style.StyleChart.Builder
-
Point size, for scatter plot etc
- pointSize - Variable in class org.deeplearning4j.ui.components.chart.style.StyleChart
-
- pointWiseConstraints - Variable in class org.deeplearning4j.nn.conf.layers.SeparableConvolution2D.Builder
-
- poll() - Method in class org.deeplearning4j.optimize.solvers.accumulation.FancyBlockingQueue
-
- poll(long, TimeUnit) - Method in class org.deeplearning4j.optimize.solvers.accumulation.FancyBlockingQueue
-
- poll(long, TimeUnit) - Method in class org.deeplearning4j.parallelism.MagicQueue
-
Deprecated.
This method is supposed to be called from managed thread, attached to specific device.
- poll() - Method in class org.deeplearning4j.parallelism.MagicQueue
-
Deprecated.
This method is supposed to be called from managed thread, attached to specific device.
- poll() - Method in class org.deeplearning4j.util.DiskBasedQueue
-
- pollEveryMillis(long) - Method in class org.deeplearning4j.perf.listener.SystemPolling.Builder
-
The interval in milliseconds in which to poll
the system for diagnostics
- PoolHelperVertex - Class in org.deeplearning4j.nn.conf.graph
-
Removes the first column and row from an input.
- PoolHelperVertex() - Constructor for class org.deeplearning4j.nn.conf.graph.PoolHelperVertex
-
- PoolHelperVertex - Class in org.deeplearning4j.nn.graph.vertex.impl
-
A custom layer for removing the first column and row from an input.
- PoolHelperVertex(ComputationGraph, String, int) - Constructor for class org.deeplearning4j.nn.graph.vertex.impl.PoolHelperVertex
-
- PoolHelperVertex(ComputationGraph, String, int, VertexIndices[], VertexIndices[]) - Constructor for class org.deeplearning4j.nn.graph.vertex.impl.PoolHelperVertex
-
- Pooling1D - Class in org.deeplearning4j.nn.conf.layers
-
1D Pooling layer.
- Pooling1D() - Constructor for class org.deeplearning4j.nn.conf.layers.Pooling1D
-
- Pooling2D - Class in org.deeplearning4j.nn.conf.layers
-
2D Pooling layer.
- Pooling2D() - Constructor for class org.deeplearning4j.nn.conf.layers.Pooling2D
-
- poolingDimensions(int...) - Method in class org.deeplearning4j.nn.conf.layers.GlobalPoolingLayer.Builder
-
Pooling dimensions.
- poolingType(PoolingType) - Method in class org.deeplearning4j.nn.conf.layers.GlobalPoolingLayer.Builder
-
- PoolingType - Enum in org.deeplearning4j.nn.conf.layers
-
Created by Alex on 17/01/2017.
- poolingType - Variable in class org.deeplearning4j.nn.conf.layers.Subsampling3DLayer.BaseSubsamplingBuilder
-
- poolingType(Subsampling3DLayer.PoolingType) - Method in class org.deeplearning4j.nn.conf.layers.Subsampling3DLayer.BaseSubsamplingBuilder
-
- poolingType - Variable in class org.deeplearning4j.nn.conf.layers.Subsampling3DLayer
-
- poolingType - Variable in class org.deeplearning4j.nn.conf.layers.SubsamplingLayer.BaseSubsamplingBuilder
-
- poolingType(SubsamplingLayer.PoolingType) - Method in class org.deeplearning4j.nn.conf.layers.SubsamplingLayer.BaseSubsamplingBuilder
-
- poolingType - Variable in class org.deeplearning4j.nn.conf.layers.SubsamplingLayer
-
- PopularityMode - Enum in org.deeplearning4j.models.sequencevectors.graph.enums
-
This enum is used in PopularityWalker, and it defines which nodes will be considered for next hop.
- popularityMode - Variable in class org.deeplearning4j.models.sequencevectors.graph.walkers.impl.PopularityWalker.Builder
-
- popularityMode - Variable in class org.deeplearning4j.models.sequencevectors.graph.walkers.impl.PopularityWalker
-
- PopularityWalker<T extends SequenceElement> - Class in org.deeplearning4j.models.sequencevectors.graph.walkers.impl
-
This is vertex popularity-based walker for SequenceVectors-based DeepWalk implementation.
- PopularityWalker() - Constructor for class org.deeplearning4j.models.sequencevectors.graph.walkers.impl.PopularityWalker
-
- PopularityWalker.Builder<T extends SequenceElement> - Class in org.deeplearning4j.models.sequencevectors.graph.walkers.impl
-
- PopularityWalker.NodeComparator - Class in org.deeplearning4j.models.sequencevectors.graph.walkers.impl
-
- port - Variable in class org.deeplearning4j.spark.parameterserver.networking.messages.SilentIntroductoryMessage
-
- PortableDataStreamCallback - Interface in org.deeplearning4j.spark.parameterserver.callbacks
-
- PortableDataStreamDataSetIterator - Class in org.deeplearning4j.spark.iterator
-
A DataSetIterator that loads serialized DataSet objects (saved with DataSet.save(OutputStream)) from
a PortableDataStream, usually obtained from SparkContext.binaryFiles()
- PortableDataStreamDataSetIterator(Iterator<PortableDataStream>) - Constructor for class org.deeplearning4j.spark.iterator.PortableDataStreamDataSetIterator
-
- PortableDataStreamDataSetIterator(Collection<PortableDataStream>) - Constructor for class org.deeplearning4j.spark.iterator.PortableDataStreamDataSetIterator
-
- PortableDataStreamMDSCallback - Interface in org.deeplearning4j.spark.parameterserver.callbacks
-
- PortableDataStreamMultiDataSetIterator - Class in org.deeplearning4j.spark.iterator
-
A DataSetIterator that loads serialized MultiDataSet objects (saved with MultiDataSet.save(OutputStream)) from
a PortableDataStream, usually obtained from SparkContext.binaryFiles()
- PortableDataStreamMultiDataSetIterator(Iterator<PortableDataStream>) - Constructor for class org.deeplearning4j.spark.iterator.PortableDataStreamMultiDataSetIterator
-
- PortableDataStreamMultiDataSetIterator(Collection<PortableDataStream>) - Constructor for class org.deeplearning4j.spark.iterator.PortableDataStreamMultiDataSetIterator
-
- pos(List<String>) - Method in class com.atilika.kuromoji.dict.GenericDictionaryEntry.Builder
-
- POS_MAP_FILENAME - Static variable in class com.atilika.kuromoji.dict.TokenInfoDictionary
-
- posInfo - Variable in class com.atilika.kuromoji.buffer.BufferEntry
-
- posInfo - Variable in class com.atilika.kuromoji.compile.TokenInfoDictionaryCompilerBase
-
- posInfos - Variable in class com.atilika.kuromoji.buffer.BufferEntry
-
- position - Variable in class org.deeplearning4j.datasets.iterator.file.BaseFileIterator
-
- position - Variable in class org.deeplearning4j.models.sequencevectors.graph.walkers.impl.RandomWalker
-
- position - Variable in class org.deeplearning4j.spark.parameterserver.iterators.VirtualDataSetIterator
-
- position - Variable in class org.deeplearning4j.text.documentiterator.FileLabelAwareIterator
-
- position - Variable in class org.deeplearning4j.text.documentiterator.FilenamesLabelAwareIterator
-
- positive() - Method in class org.deeplearning4j.eval.Evaluation
-
Returns all of the positive guesses:
true positive + false negative
- PoStagger - Class in org.deeplearning4j.text.annotator
-
- PoStagger() - Constructor for class org.deeplearning4j.text.annotator.PoStagger
-
Initializes a new instance.
- postApply(Layer, String, INDArray, INDArray) - Method in class org.deeplearning4j.nn.updater.UpdaterBlock
-
Apply L1 and L2 regularization, if necessary.
- postFirstStep(INDArray) - Method in class org.deeplearning4j.optimize.solvers.BaseOptimizer
-
- postInit() - Method in class org.deeplearning4j.parallelism.trainer.DefaultTrainer
-
This method does post-initialization configuration of Model.
- postInit() - Method in class org.deeplearning4j.parallelism.trainer.SymmetricTrainer
-
- postProcessAnnotations(Span[], AnnotationFS[]) - Method in class org.deeplearning4j.text.tokenization.tokenizer.ConcurrentTokenizer
-
- postReport(WebTarget, Entity) - Method in class org.deeplearning4j.ui.WebReporter
-
This method immediately sends UI report to specified target using POST request
- postStep(INDArray) - Method in interface org.deeplearning4j.optimize.api.ConvexOptimizer
-
After the step has been made, do an action
- postStep(INDArray) - Method in class org.deeplearning4j.optimize.solvers.BaseOptimizer
-
Post step to update searchDirection with new gradient and parameter information
- postStep(INDArray) - Method in class org.deeplearning4j.optimize.solvers.ConjugateGradient
-
- postStep(INDArray) - Method in class org.deeplearning4j.optimize.solvers.LBFGS
-
- postStep(INDArray) - Method in class org.deeplearning4j.optimize.solvers.LineGradientDescent
-
- postStep(INDArray) - Method in class org.deeplearning4j.optimize.solvers.StochasticGradientDescent
-
- postUpdate(DataSet, Model) - Method in interface org.deeplearning4j.spark.api.TrainingHook
-
A hook method for post update
- postUpdate(MultiDataSet, Model) - Method in interface org.deeplearning4j.spark.api.TrainingHook
-
A hook method for post update
- postUpdate(DataSet, Model) - Method in class org.deeplearning4j.spark.parameterserver.ParameterServerTrainingHook
-
A hook method for post update
- postUpdate(MultiDataSet, Model) - Method in class org.deeplearning4j.spark.parameterserver.ParameterServerTrainingHook
-
A hook method for post update
- PosUimaTokenizer - Class in org.deeplearning4j.text.tokenization.tokenizer
-
Filter by part of speech tag.
- PosUimaTokenizer(String, AnalysisEngine, Collection<String>) - Constructor for class org.deeplearning4j.text.tokenization.tokenizer.PosUimaTokenizer
-
- PosUimaTokenizer(String, AnalysisEngine, Collection<String>, boolean) - Constructor for class org.deeplearning4j.text.tokenization.tokenizer.PosUimaTokenizer
-
- PosUimaTokenizerFactory - Class in org.deeplearning4j.text.tokenization.tokenizerfactory
-
Creates a tokenizer that filters by
part of speech tags
- PosUimaTokenizerFactory(Collection<String>, boolean) - Constructor for class org.deeplearning4j.text.tokenization.tokenizerfactory.PosUimaTokenizerFactory
-
- PosUimaTokenizerFactory(Collection<String>) - Constructor for class org.deeplearning4j.text.tokenization.tokenizerfactory.PosUimaTokenizerFactory
-
- PosUimaTokenizerFactory(AnalysisEngine, Collection<String>) - Constructor for class org.deeplearning4j.text.tokenization.tokenizerfactory.PosUimaTokenizerFactory
-
- posValues - Variable in class com.atilika.kuromoji.dict.TokenInfoDictionary
-
- preApply(Layer, Gradient, int) - Method in class org.deeplearning4j.nn.updater.BaseMultiLayerUpdater
-
Pre-apply: Apply gradient normalization/clipping
- preciseWeightInit - Variable in class org.deeplearning4j.models.sequencevectors.SequenceVectors.Builder
-
- precision(Integer) - Method in class org.deeplearning4j.eval.Evaluation
-
Returns the precision for a given class label
- precision(Integer, double) - Method in class org.deeplearning4j.eval.Evaluation
-
Returns the precision for a given label
- precision() - Method in class org.deeplearning4j.eval.Evaluation
-
Precision based on guesses so far.
Note: value returned will differ depending on number of classes and settings.
1.
- precision(EvaluationAveraging) - Method in class org.deeplearning4j.eval.Evaluation
-
Calculate the average precision for all classes.
- precision(int) - Method in class org.deeplearning4j.eval.EvaluationBinary
-
Get the precision (tp / (tp + fp)) for the specified output
- precision(long, long, double) - Static method in class org.deeplearning4j.eval.EvaluationUtils
-
Calculate the precision from true positive and false positive counts
- PrecisionRecallCurve - Class in org.deeplearning4j.eval.curves
-
Precision recall curve: A set of (recall, precision) points and different thresholds
- PrecisionRecallCurve(double[], double[], double[], int[], int[], int[], int) - Constructor for class org.deeplearning4j.eval.curves.PrecisionRecallCurve
-
- PrecisionRecallCurve.Confusion - Class in org.deeplearning4j.eval.curves
-
- PrecisionRecallCurve.Point - Class in org.deeplearning4j.eval.curves
-
- predict(String) - Method in class org.deeplearning4j.models.paragraphvectors.ParagraphVectors
-
Deprecated.
- predict(LabelledDocument) - Method in class org.deeplearning4j.models.paragraphvectors.ParagraphVectors
-
This method predicts label of the document.
- predict(List<VocabWord>) - Method in class org.deeplearning4j.models.paragraphvectors.ParagraphVectors
-
This method predicts label of the document.
- predict(INDArray) - Method in interface org.deeplearning4j.nn.api.Classifier
-
Takes in a list of examples
For each row, returns a label
- predict(DataSet) - Method in interface org.deeplearning4j.nn.api.Classifier
-
Takes in a DataSet of examples
For each row, returns a label
- predict(INDArray) - Method in class org.deeplearning4j.nn.layers.BaseOutputLayer
-
Returns the predictions for each example in the dataset
- predict(DataSet) - Method in class org.deeplearning4j.nn.layers.BaseOutputLayer
-
Return predicted label names
- predict(INDArray) - Method in class org.deeplearning4j.nn.layers.convolution.CnnLossLayer
-
- predict(DataSet) - Method in class org.deeplearning4j.nn.layers.convolution.CnnLossLayer
-
- predict(INDArray) - Method in class org.deeplearning4j.nn.layers.LossLayer
-
Returns the predictions for each example in the dataset
- predict(DataSet) - Method in class org.deeplearning4j.nn.layers.LossLayer
-
Return predicted label names
- predict(INDArray) - Method in class org.deeplearning4j.nn.layers.objdetect.Yolo2OutputLayer
-
- predict(DataSet) - Method in class org.deeplearning4j.nn.layers.objdetect.Yolo2OutputLayer
-
- predict(INDArray) - Method in class org.deeplearning4j.nn.layers.recurrent.RnnLossLayer
-
- predict(DataSet) - Method in class org.deeplearning4j.nn.layers.recurrent.RnnLossLayer
-
- predict(INDArray) - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
-
Returns the predictions for each example in the dataset
- predict(DataSet) - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
-
Return predicted label names
- predict(Matrix) - Method in class org.deeplearning4j.spark.impl.multilayer.SparkDl4jMultiLayer
-
Predict the given feature matrix
- predict(Vector) - Method in class org.deeplearning4j.spark.impl.multilayer.SparkDl4jMultiLayer
-
Predict the given vector
- Prediction - Class in org.deeplearning4j.eval.meta
-
Prediction: a prediction for classification, used with the
Evaluation class.
- Prediction() - Constructor for class org.deeplearning4j.eval.meta.Prediction
-
- prediction() - Method in class org.deeplearning4j.nn.layers.feedforward.autoencoder.recursive.Tree
-
- predictSeveral(LabelledDocument, int) - Method in class org.deeplearning4j.models.paragraphvectors.ParagraphVectors
-
Predict several labels based on the document.
- predictSeveral(String, int) - Method in class org.deeplearning4j.models.paragraphvectors.ParagraphVectors
-
Predict several labels based on the document.
- predictSeveral(List<VocabWord>, int) - Method in class org.deeplearning4j.models.paragraphvectors.ParagraphVectors
-
Predict several labels based on the document.
- prefetchBuffer(int) - Method in class org.deeplearning4j.parallelism.ParallelWrapper.Builder
-
Size of prefetch buffer that will be used for background data prefetching.
- PrefetchingSentenceIterator - Class in org.deeplearning4j.text.sentenceiterator
-
Deprecated.
- PrefetchingSentenceIterator.Builder - Class in org.deeplearning4j.text.sentenceiterator
-
Deprecated.
- prefetchNumBatches - Variable in class org.deeplearning4j.spark.api.WorkerConfiguration
-
- prefetchNumBatches - Variable in class org.deeplearning4j.spark.impl.paramavg.ParameterAveragingTrainingMaster.Builder
-
- prefetchNumBatches - Variable in class org.deeplearning4j.spark.impl.paramavg.ParameterAveragingTrainingMaster
-
- prefetchSize - Variable in class org.deeplearning4j.datasets.iterator.AsyncDataSetIterator
-
- prefetchSize - Variable in class org.deeplearning4j.datasets.iterator.AsyncMultiDataSetIterator
-
- prefetchSize - Variable in class org.deeplearning4j.parallelism.ParallelWrapper.Builder
-
- prefetchSize - Variable in class org.deeplearning4j.parallelism.ParallelWrapper
-
- prefetchSize - Variable in class org.deeplearning4j.spark.parameterserver.conf.SharedTrainingConfiguration
-
- preloadedDataSet - Variable in class org.deeplearning4j.spark.iterator.BaseDataSetIterator
-
- preOutput - Variable in class org.deeplearning4j.nn.layers.AbstractLayer
-
- preOutput(boolean, LayerWorkspaceMgr) - Method in class org.deeplearning4j.nn.layers.BaseLayer
-
- preOutput(boolean, boolean, LayerWorkspaceMgr) - Method in class org.deeplearning4j.nn.layers.convolution.Convolution1DLayer
-
- preOutput(boolean, LayerWorkspaceMgr) - Method in class org.deeplearning4j.nn.layers.convolution.Convolution3DLayer
-
- preOutput(boolean, boolean, LayerWorkspaceMgr) - Method in class org.deeplearning4j.nn.layers.convolution.Convolution3DLayer
-
- preOutput(INDArray, INDArray, INDArray, int[], int[], int[], ConvolutionLayer.AlgoMode, ConvolutionLayer.FwdAlgo, ConvolutionMode, int[], LayerWorkspaceMgr) - Method in interface org.deeplearning4j.nn.layers.convolution.ConvolutionHelper
-
- preOutput(boolean, boolean, LayerWorkspaceMgr) - Method in class org.deeplearning4j.nn.layers.convolution.ConvolutionLayer
-
PreOutput method that also returns the im2col2d array (if being called for backprop), as this can be re-used
instead of being calculated again.
- preOutput(INDArray, INDArray, INDArray, int[], int[], int[], ConvolutionLayer.AlgoMode, ConvolutionLayer.FwdAlgo, ConvolutionMode, int[], LayerWorkspaceMgr) - Method in class org.deeplearning4j.nn.layers.convolution.CudnnConvolutionHelper
-
- preOutput(boolean, boolean, LayerWorkspaceMgr) - Method in class org.deeplearning4j.nn.layers.convolution.Deconvolution2DLayer
-
- preOutput(boolean, boolean, LayerWorkspaceMgr) - Method in class org.deeplearning4j.nn.layers.convolution.DepthwiseConvolution2DLayer
-
- preOutput(boolean, boolean, LayerWorkspaceMgr) - Method in class org.deeplearning4j.nn.layers.convolution.SeparableConvolution2DLayer
-
- preOutput(boolean, boolean, LayerWorkspaceMgr) - Method in class org.deeplearning4j.nn.layers.convolution.SpaceToBatch
-
- preOutput(boolean, boolean, LayerWorkspaceMgr) - Method in class org.deeplearning4j.nn.layers.convolution.SpaceToDepth
-
- preOutput(boolean, boolean, LayerWorkspaceMgr) - Method in class org.deeplearning4j.nn.layers.convolution.upsampling.Upsampling1D
-
- preOutput(boolean, boolean, LayerWorkspaceMgr) - Method in class org.deeplearning4j.nn.layers.convolution.upsampling.Upsampling2D
-
- preOutput(boolean, boolean, LayerWorkspaceMgr) - Method in class org.deeplearning4j.nn.layers.convolution.upsampling.Upsampling3D
-
- preOutput(boolean, LayerWorkspaceMgr) - Method in class org.deeplearning4j.nn.layers.feedforward.elementwise.ElementWiseMultiplicationLayer
-
- preOutput(boolean, LayerWorkspaceMgr) - Method in class org.deeplearning4j.nn.layers.feedforward.embedding.EmbeddingLayer
-
- preOutput(boolean, LayerWorkspaceMgr) - Method in class org.deeplearning4j.nn.layers.feedforward.embedding.EmbeddingSequenceLayer
-
- preOutput(INDArray, Layer.TrainingMode, LayerWorkspaceMgr) - Method in class org.deeplearning4j.nn.layers.normalization.BatchNormalization
-
- preOutput(INDArray, boolean, int[], INDArray, INDArray, INDArray, INDArray, double, double, LayerWorkspaceMgr) - Method in interface org.deeplearning4j.nn.layers.normalization.BatchNormalizationHelper
-
- preOutput(INDArray, boolean, int[], INDArray, INDArray, INDArray, INDArray, double, double, LayerWorkspaceMgr) - Method in class org.deeplearning4j.nn.layers.normalization.CudnnBatchNormalizationHelper
-
- preOutput(boolean, LayerWorkspaceMgr) - Method in class org.deeplearning4j.nn.layers.variational.VariationalAutoencoder
-
- preOutput2d(boolean, LayerWorkspaceMgr) - Method in class org.deeplearning4j.nn.layers.BaseOutputLayer
-
- preOutput2d(boolean, LayerWorkspaceMgr) - Method in class org.deeplearning4j.nn.layers.ocnn.OCNNOutputLayer
-
- preOutput2d(boolean, LayerWorkspaceMgr) - Method in class org.deeplearning4j.nn.layers.recurrent.RnnOutputLayer
-
- preOutput4d(boolean, boolean, LayerWorkspaceMgr) - Method in class org.deeplearning4j.nn.layers.convolution.Convolution1DLayer
-
- preOutput4d(boolean, boolean, LayerWorkspaceMgr) - Method in class org.deeplearning4j.nn.layers.convolution.ConvolutionLayer
-
preOutput4d: Used so that ConvolutionLayer subclasses (such as Convolution1DLayer) can maintain their standard
non-4d preOutput method, while overriding this to return 4d activations (for use in backprop) without modifying
the public API
- prepareNetworkAndStuff(SparkDl4jMultiLayer, SparkComputationGraph) - Method in class org.deeplearning4j.spark.parameterserver.training.SharedTrainingMaster
-
- preProcess(MultiDataSet) - Method in class org.deeplearning4j.datasets.iterator.CombinedMultiDataSetPreProcessor
-
- preProcess(DataSet) - Method in class org.deeplearning4j.datasets.iterator.CombinedPreProcessor
-
Pre process a dataset sequentially
- preProcess(DataSet) - Method in class org.deeplearning4j.datasets.iterator.DummyPreProcessor
-
Pre process a dataset
- preProcess(INDArray, int, LayerWorkspaceMgr) - Method in interface org.deeplearning4j.nn.conf.InputPreProcessor
-
Pre preProcess input/activations for a multi layer network
- preProcess(INDArray, int, LayerWorkspaceMgr) - Method in class org.deeplearning4j.nn.conf.preprocessor.BinomialSamplingPreProcessor
-
- preProcess(INDArray, int, LayerWorkspaceMgr) - Method in class org.deeplearning4j.nn.conf.preprocessor.Cnn3DToFeedForwardPreProcessor
-
- preProcess(INDArray, int, LayerWorkspaceMgr) - Method in class org.deeplearning4j.nn.conf.preprocessor.CnnToFeedForwardPreProcessor
-
- preProcess(INDArray, int, LayerWorkspaceMgr) - Method in class org.deeplearning4j.nn.conf.preprocessor.CnnToRnnPreProcessor
-
- preProcess(INDArray, int, LayerWorkspaceMgr) - Method in class org.deeplearning4j.nn.conf.preprocessor.ComposableInputPreProcessor
-
- preProcess(INDArray, int, LayerWorkspaceMgr) - Method in class org.deeplearning4j.nn.conf.preprocessor.FeedForwardToCnn3DPreProcessor
-
- preProcess(INDArray, int, LayerWorkspaceMgr) - Method in class org.deeplearning4j.nn.conf.preprocessor.FeedForwardToCnnPreProcessor
-
- preProcess(INDArray, int, LayerWorkspaceMgr) - Method in class org.deeplearning4j.nn.conf.preprocessor.FeedForwardToRnnPreProcessor
-
- preProcess(INDArray, int, LayerWorkspaceMgr) - Method in class org.deeplearning4j.nn.conf.preprocessor.RnnToCnnPreProcessor
-
- preProcess(INDArray, int, LayerWorkspaceMgr) - Method in class org.deeplearning4j.nn.conf.preprocessor.RnnToFeedForwardPreProcessor
-
- preProcess(INDArray, int, LayerWorkspaceMgr) - Method in class org.deeplearning4j.nn.conf.preprocessor.UnitVarianceProcessor
-
- preProcess(INDArray, int, LayerWorkspaceMgr) - Method in class org.deeplearning4j.nn.conf.preprocessor.ZeroMeanAndUnitVariancePreProcessor
-
- preProcess(INDArray, int, LayerWorkspaceMgr) - Method in class org.deeplearning4j.nn.conf.preprocessor.ZeroMeanPrePreProcessor
-
- preProcess(INDArray, int, LayerWorkspaceMgr) - Method in class org.deeplearning4j.nn.modelimport.keras.preprocessors.KerasFlattenRnnPreprocessor
-
- preProcess(INDArray, int, LayerWorkspaceMgr) - Method in class org.deeplearning4j.nn.modelimport.keras.preprocessors.PermutePreprocessor
-
- preProcess(INDArray, int, LayerWorkspaceMgr) - Method in class org.deeplearning4j.nn.modelimport.keras.preprocessors.ReshapePreprocessor
-
- preProcess(INDArray, int, LayerWorkspaceMgr) - Method in class org.deeplearning4j.nn.modelimport.keras.preprocessors.TensorFlowCnnToFeedForwardPreProcessor
-
- preProcess(String) - Method in interface org.deeplearning4j.text.sentenceiterator.SentencePreProcessor
-
Pre process a sentence
- preProcess(String) - Method in class org.deeplearning4j.text.tokenization.tokenizer.preprocessor.CommonPreprocessor
-
- preProcess(String) - Method in class org.deeplearning4j.text.tokenization.tokenizer.preprocessor.CustomStemmingPreprocessor
-
- preProcess(String) - Method in class org.deeplearning4j.text.tokenization.tokenizer.preprocessor.EmbeddedStemmingPreprocessor
-
- preProcess(String) - Method in class org.deeplearning4j.text.tokenization.tokenizer.preprocessor.EndingPreProcessor
-
- preProcess(String) - Method in class org.deeplearning4j.text.tokenization.tokenizer.preprocessor.LowCasePreProcessor
-
Pre process a token
- preProcess(String) - Method in class org.deeplearning4j.text.tokenization.tokenizer.preprocessor.StemmingPreprocessor
-
- preProcess(String) - Method in interface org.deeplearning4j.text.tokenization.tokenizer.TokenPreProcess
-
Pre process a token
- preProcessLine() - Method in interface org.deeplearning4j.optimize.api.ConvexOptimizer
-
Pre preProcess a line before an iteration
- preProcessLine() - Method in class org.deeplearning4j.optimize.solvers.BaseOptimizer
-
Pre preProcess to setup initial searchDirection approximation
- preProcessLine() - Method in class org.deeplearning4j.optimize.solvers.ConjugateGradient
-
- preProcessLine() - Method in class org.deeplearning4j.optimize.solvers.LBFGS
-
- preProcessLine() - Method in class org.deeplearning4j.optimize.solvers.LineGradientDescent
-
- preProcessLine() - Method in class org.deeplearning4j.optimize.solvers.StochasticGradientDescent
-
- preProcessor - Variable in class org.deeplearning4j.datasets.datavec.RecordReaderDataSetIterator.Builder
-
- preProcessor(DataSetPreProcessor) - Method in class org.deeplearning4j.datasets.datavec.RecordReaderDataSetIterator.Builder
-
Optional arg.
- preProcessor - Variable in class org.deeplearning4j.datasets.datavec.RecordReaderDataSetIterator
-
- preProcessor - Variable in class org.deeplearning4j.datasets.iterator.BaseDatasetIterator
-
- preProcessor - Variable in class org.deeplearning4j.datasets.iterator.file.BaseFileIterator
-
- preProcessor - Variable in class org.deeplearning4j.datasets.iterator.impl.EmnistDataSetIterator
-
- preProcessor - Variable in class org.deeplearning4j.datasets.iterator.impl.TinyImageNetDataSetIterator
-
- preProcessor - Variable in class org.deeplearning4j.datasets.iterator.impl.UciSequenceDataSetIterator
-
- preProcessor - Variable in class org.deeplearning4j.datasets.iterator.MultiDataSetWrapperIterator
-
- preProcessor - Variable in class org.deeplearning4j.datasets.iterator.MultipleEpochsIterator
-
Deprecated.
- preprocessor - Variable in class org.deeplearning4j.spark.iterator.BaseDataSetIterator
-
- preProcessor - Variable in class org.deeplearning4j.text.sentenceiterator.BaseSentenceIterator
-
- PREPROCESSOR_BIN - Static variable in class org.deeplearning4j.util.ModelSerializer
-
- PreprocessorVertex - Class in org.deeplearning4j.nn.conf.graph
-
PreprocessorVertex is a simple adaptor class that allows a
InputPreProcessor to be used in a ComputationGraph
GraphVertex, without it being associated with a layer.
- PreprocessorVertex(InputPreProcessor) - Constructor for class org.deeplearning4j.nn.conf.graph.PreprocessorVertex
-
- PreprocessorVertex - Class in org.deeplearning4j.nn.graph.vertex.impl
-
PreprocessorVertex is a simple adaptor class that allows a
InputPreProcessor to be used in a ComputationGraph
GraphVertex, without it being associated with a layer.
- PreprocessorVertex(ComputationGraph, String, int, InputPreProcessor) - Constructor for class org.deeplearning4j.nn.graph.vertex.impl.PreprocessorVertex
-
- PreprocessorVertex(ComputationGraph, String, int, VertexIndices[], VertexIndices[], InputPreProcessor) - Constructor for class org.deeplearning4j.nn.graph.vertex.impl.PreprocessorVertex
-
- presetTables() - Method in class org.deeplearning4j.models.node2vec.Node2Vec.Builder
-
Deprecated.
- presetTables() - Method in class org.deeplearning4j.models.sequencevectors.SequenceVectors.Builder
-
This method creates new WeightLookupTable and VocabCache if there were none set
- pretrain(SequenceIterator<T>) - Method in interface org.deeplearning4j.models.embeddings.learning.ElementsLearningAlgorithm
-
- pretrain(SequenceIterator<T>) - Method in class org.deeplearning4j.models.embeddings.learning.impl.elements.CBOW
-
CBOW doesn't involve any pretraining
- pretrain(SequenceIterator<T>) - Method in class org.deeplearning4j.models.embeddings.learning.impl.elements.GloVe
-
pretrain is used to build CoOccurrence matrix for GloVe algorithm
- pretrain(SequenceIterator<T>) - Method in class org.deeplearning4j.models.embeddings.learning.impl.elements.SkipGram
-
SkipGram doesn't involves any pretraining
- pretrain(SequenceIterator<T>) - Method in class org.deeplearning4j.models.embeddings.learning.impl.sequence.DBOW
-
DBOW doesn't involves any pretraining
- pretrain(SequenceIterator<T>) - Method in class org.deeplearning4j.models.embeddings.learning.impl.sequence.DM
-
- pretrain(SequenceIterator<T>) - Method in interface org.deeplearning4j.models.embeddings.learning.SequenceLearningAlgorithm
-
- pretrain - Variable in class org.deeplearning4j.nn.conf.ComputationGraphConfiguration.GraphBuilder
-
- pretrain(boolean) - Method in class org.deeplearning4j.nn.conf.ComputationGraphConfiguration.GraphBuilder
-
Whether to do layerwise pre training or not
- pretrain - Variable in class org.deeplearning4j.nn.conf.ComputationGraphConfiguration
-
- pretrain - Variable in class org.deeplearning4j.nn.conf.MultiLayerConfiguration.Builder
-
- pretrain(boolean) - Method in class org.deeplearning4j.nn.conf.MultiLayerConfiguration.Builder
-
Whether to do pre train or not
- pretrain - Variable in class org.deeplearning4j.nn.conf.MultiLayerConfiguration
-
- pretrain - Variable in class org.deeplearning4j.nn.conf.NeuralNetConfiguration.Builder
-
- pretrain(boolean) - Method in class org.deeplearning4j.nn.conf.NeuralNetConfiguration.ListBuilder
-
- pretrain - Variable in class org.deeplearning4j.nn.conf.NeuralNetConfiguration
-
- pretrain(DataSetIterator) - Method in class org.deeplearning4j.nn.graph.ComputationGraph
-
Pretrain network with a single input and single output.
- pretrain(MultiDataSetIterator) - Method in class org.deeplearning4j.nn.graph.ComputationGraph
-
Pretrain network with multiple inputs and/or outputs
- pretrain(DataSetIterator) - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
-
Perform layerwise pretraining on all pre-trainable layers in the network (VAEs, Autoencoders, etc)
Note that pretraining will be performed on one layer after the other, resetting the DataSetIterator between iterations.
For multiple epochs per layer, appropriately wrap the iterator (for example, a MultipleEpochsIterator) or train
each layer manually using
MultiLayerNetwork.pretrainLayer(int, DataSetIterator)
- pretrain(boolean) - Method in class org.deeplearning4j.nn.transferlearning.FineTuneConfiguration.Builder
-
- pretrain - Variable in class org.deeplearning4j.nn.transferlearning.FineTuneConfiguration
-
- pretrain(SequenceIterator<ShallowSequenceElement>) - Method in class org.deeplearning4j.spark.models.sequencevectors.learning.elements.BaseSparkLearningAlgorithm
-
- pretrain(SequenceIterator<ShallowSequenceElement>) - Method in class org.deeplearning4j.spark.models.sequencevectors.learning.sequence.BaseSparkSequenceLearningAlgorithm
-
- pretrainedAvailable(PretrainedType) - Method in class org.deeplearning4j.zoo.ZooModel
-
- pretrainedChecksum(PretrainedType) - Method in interface org.deeplearning4j.zoo.InstantiableModel
-
- pretrainedChecksum(PretrainedType) - Method in class org.deeplearning4j.zoo.model.AlexNet
-
- pretrainedChecksum(PretrainedType) - Method in class org.deeplearning4j.zoo.model.Darknet19
-
- pretrainedChecksum(PretrainedType) - Method in class org.deeplearning4j.zoo.model.FaceNetNN4Small2
-
- pretrainedChecksum(PretrainedType) - Method in class org.deeplearning4j.zoo.model.InceptionResNetV1
-
- pretrainedChecksum(PretrainedType) - Method in class org.deeplearning4j.zoo.model.LeNet
-
- pretrainedChecksum(PretrainedType) - Method in class org.deeplearning4j.zoo.model.NASNet
-
- pretrainedChecksum(PretrainedType) - Method in class org.deeplearning4j.zoo.model.ResNet50
-
- pretrainedChecksum(PretrainedType) - Method in class org.deeplearning4j.zoo.model.SimpleCNN
-
- pretrainedChecksum(PretrainedType) - Method in class org.deeplearning4j.zoo.model.SqueezeNet
-
- pretrainedChecksum(PretrainedType) - Method in class org.deeplearning4j.zoo.model.TextGenerationLSTM
-
- pretrainedChecksum(PretrainedType) - Method in class org.deeplearning4j.zoo.model.TinyYOLO
-
- pretrainedChecksum(PretrainedType) - Method in class org.deeplearning4j.zoo.model.UNet
-
- pretrainedChecksum(PretrainedType) - Method in class org.deeplearning4j.zoo.model.VGG16
-
- pretrainedChecksum(PretrainedType) - Method in class org.deeplearning4j.zoo.model.VGG19
-
- pretrainedChecksum(PretrainedType) - Method in class org.deeplearning4j.zoo.model.Xception
-
- pretrainedChecksum(PretrainedType) - Method in class org.deeplearning4j.zoo.model.YOLO2
-
- PretrainedType - Enum in org.deeplearning4j.zoo
-
Enumerator for choosing different models, and different types of models.
- pretrainedUrl(PretrainedType) - Method in interface org.deeplearning4j.zoo.InstantiableModel
-
- pretrainedUrl(PretrainedType) - Method in class org.deeplearning4j.zoo.model.AlexNet
-
- pretrainedUrl(PretrainedType) - Method in class org.deeplearning4j.zoo.model.Darknet19
-
- pretrainedUrl(PretrainedType) - Method in class org.deeplearning4j.zoo.model.FaceNetNN4Small2
-
- pretrainedUrl(PretrainedType) - Method in class org.deeplearning4j.zoo.model.InceptionResNetV1
-
- pretrainedUrl(PretrainedType) - Method in class org.deeplearning4j.zoo.model.LeNet
-
- pretrainedUrl(PretrainedType) - Method in class org.deeplearning4j.zoo.model.NASNet
-
- pretrainedUrl(PretrainedType) - Method in class org.deeplearning4j.zoo.model.ResNet50
-
- pretrainedUrl(PretrainedType) - Method in class org.deeplearning4j.zoo.model.SimpleCNN
-
- pretrainedUrl(PretrainedType) - Method in class org.deeplearning4j.zoo.model.SqueezeNet
-
- pretrainedUrl(PretrainedType) - Method in class org.deeplearning4j.zoo.model.TextGenerationLSTM
-
- pretrainedUrl(PretrainedType) - Method in class org.deeplearning4j.zoo.model.TinyYOLO
-
- pretrainedUrl(PretrainedType) - Method in class org.deeplearning4j.zoo.model.UNet
-
- pretrainedUrl(PretrainedType) - Method in class org.deeplearning4j.zoo.model.VGG16
-
- pretrainedUrl(PretrainedType) - Method in class org.deeplearning4j.zoo.model.VGG19
-
- pretrainedUrl(PretrainedType) - Method in class org.deeplearning4j.zoo.model.Xception
-
- pretrainedUrl(PretrainedType) - Method in class org.deeplearning4j.zoo.model.YOLO2
-
- pretrainLayer(String, DataSetIterator) - Method in class org.deeplearning4j.nn.graph.ComputationGraph
-
Pretrain a specified layer with the given DataSetIterator
- pretrainLayer(String, MultiDataSetIterator) - Method in class org.deeplearning4j.nn.graph.ComputationGraph
-
Pretrain a specified layer with the given MultiDataSetIterator
- pretrainLayer(int, DataSetIterator) - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
-
Perform layerwise unsupervised training on a single pre-trainable layer in the network (VAEs, Autoencoders, etc)
If the specified layer index (0 to numLayers - 1) is not a pretrainable layer, this is a no-op.
- pretrainLayer(int, INDArray) - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
-
Perform layerwise unsupervised training on a single pre-trainable layer in the network (VAEs, Autoencoders, etc)
If the specified layer index (0 to numLayers - 1) is not a pretrainable layer, this is a no-op.
- PretrainParamInitializer - Class in org.deeplearning4j.nn.params
-
Pretrain weight initializer.
- PretrainParamInitializer() - Constructor for class org.deeplearning4j.nn.params.PretrainParamInitializer
-
- preUpdate(DataSet, Model) - Method in interface org.deeplearning4j.spark.api.TrainingHook
-
A hook method for pre update.
- preUpdate(MultiDataSet, Model) - Method in interface org.deeplearning4j.spark.api.TrainingHook
-
A hook method for pre update.
- preUpdate(DataSet, Model) - Method in class org.deeplearning4j.spark.parameterserver.ParameterServerTrainingHook
-
A hook method for pre update.
- preUpdate(MultiDataSet, Model) - Method in class org.deeplearning4j.spark.parameterserver.ParameterServerTrainingHook
-
A hook method for pre update.
- prev() - Method in class org.deeplearning4j.datasets.mnist.MnistDbFile
-
Move to the previous entry.
- prevAct - Variable in class org.deeplearning4j.nn.layers.recurrent.FwdPassReturn
-
- prevImage() - Method in class org.deeplearning4j.datasets.mnist.MnistImageFile
-
Move the cursor to the previous image.
- previous() - Method in class org.deeplearning4j.models.glove.count.RoundCount
-
- prevMemCell - Variable in class org.deeplearning4j.nn.layers.recurrent.FwdPassReturn
-
- PRINT_INDENT - Static variable in interface org.deeplearning4j.spark.api.stats.SparkTrainingStats
-
- printConfiguration() - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
-
Prints the configuration
- printFeatures(String[][]) - Method in class com.atilika.kuromoji.compile.UnknownDictionaryCompiler
-
- printFeatureTree(String, float[]) - Static method in class org.ansj.app.crf.Model
-
增加特征到特征数中
- printGraph() - Method in class org.ansj.util.Graph
-
对graph进行调试用的
- println(String) - Static method in class com.atilika.kuromoji.compile.ProgressLog
-
- printOutProjectedMemoryUse(long, int, int) - Static method in class org.deeplearning4j.models.embeddings.loader.WordVectorSerializer
-
- probRound(double, Random) - Static method in class org.deeplearning4j.clustering.util.MathUtils
-
Rounds a double to the next nearest integer value in a probabilistic
fashion (e.g.
- probToLogOdds(double) - Static method in class org.deeplearning4j.clustering.util.MathUtils
-
Returns the log-odds for a given probability.
- process(CAS) - Method in class org.deeplearning4j.text.annotator.PoStagger
-
Performs pos-tagging on the given tcas object.
- process(JCas) - Method in class org.deeplearning4j.text.annotator.SentenceAnnotator
-
- process(JCas) - Method in class org.deeplearning4j.text.annotator.StemmerAnnotator
-
- process(CAS) - Method in class org.deeplearning4j.text.tokenization.tokenizer.ConcurrentTokenizer
-
- process(String) - Method in class org.deeplearning4j.text.uima.UimaResource
-
Use the given analysis engine and process the given text
You must release the return cas yourself
- processEvent(ListenerEvent, SequenceVectors<T>, long) - Method in interface org.deeplearning4j.models.sequencevectors.interfaces.VectorsListener
-
This method is called at each epoch end
- processEvent(ListenerEvent, SequenceVectors<T>, long) - Method in class org.deeplearning4j.models.sequencevectors.listeners.ScoreListener
-
Deprecated.
- processEvent(ListenerEvent, SequenceVectors<T>, long) - Method in class org.deeplearning4j.models.sequencevectors.listeners.SerializingListener
-
This method is called at each epoch end
- processEvent(ListenerEvent, SequenceVectors<T>, long) - Method in class org.deeplearning4j.models.sequencevectors.listeners.SimilarityListener
-
- processing - Variable in class org.deeplearning4j.models.sequencevectors.transformers.impl.iterables.ParallelTransformerIterator
-
- processLine(String) - Method in interface org.deeplearning4j.graph.data.EdgeLineProcessor
-
Process a line of text into an edge.
- processLine(String) - Method in class org.deeplearning4j.graph.data.impl.DelimitedEdgeLineProcessor
-
- processLine(String) - Method in class org.deeplearning4j.graph.data.impl.WeightedEdgeLineProcessor
-
- processMessage() - Method in class org.deeplearning4j.spark.parameterserver.networking.messages.SilentIntroductoryConfirmation
-
- processMessage() - Method in class org.deeplearning4j.spark.parameterserver.networking.messages.SilentIntroductoryMessage
-
- processMessage() - Method in class org.deeplearning4j.spark.parameterserver.networking.messages.SilentUpdatesMessage
-
- processMinibatch(DataSet, MultiLayerNetwork, boolean) - Method in interface org.deeplearning4j.spark.api.TrainingWorker
-
Process (fit) a minibatch for a MultiLayerNetwork
- processMinibatch(DataSet, ComputationGraph, boolean) - Method in interface org.deeplearning4j.spark.api.TrainingWorker
-
Process (fit) a minibatch for a ComputationGraph
- processMinibatch(MultiDataSet, ComputationGraph, boolean) - Method in interface org.deeplearning4j.spark.api.TrainingWorker
-
Process (fit) a minibatch for a ComputationGraph using a MultiDataSet
- processMinibatch(DataSet, MultiLayerNetwork, boolean) - Method in class org.deeplearning4j.spark.impl.paramavg.ParameterAveragingTrainingWorker
-
- processMinibatch(DataSet, ComputationGraph, boolean) - Method in class org.deeplearning4j.spark.impl.paramavg.ParameterAveragingTrainingWorker
-
- processMinibatch(MultiDataSet, ComputationGraph, boolean) - Method in class org.deeplearning4j.spark.impl.paramavg.ParameterAveragingTrainingWorker
-
- processMinibatch(DataSet, MultiLayerNetwork, boolean) - Method in class org.deeplearning4j.spark.parameterserver.training.SharedTrainingWorker
-
- processMinibatch(DataSet, ComputationGraph, boolean) - Method in class org.deeplearning4j.spark.parameterserver.training.SharedTrainingWorker
-
- processMinibatch(MultiDataSet, ComputationGraph, boolean) - Method in class org.deeplearning4j.spark.parameterserver.training.SharedTrainingWorker
-
- processMinibatchWithStats(DataSet, MultiLayerNetwork, boolean) - Method in interface org.deeplearning4j.spark.api.TrainingWorker
-
- processMinibatchWithStats(DataSet, ComputationGraph, boolean) - Method in interface org.deeplearning4j.spark.api.TrainingWorker
-
- processMinibatchWithStats(MultiDataSet, ComputationGraph, boolean) - Method in interface org.deeplearning4j.spark.api.TrainingWorker
-
- processMinibatchWithStats(DataSet, MultiLayerNetwork, boolean) - Method in class org.deeplearning4j.spark.impl.paramavg.ParameterAveragingTrainingWorker
-
- processMinibatchWithStats(DataSet, ComputationGraph, boolean) - Method in class org.deeplearning4j.spark.impl.paramavg.ParameterAveragingTrainingWorker
-
- processMinibatchWithStats(MultiDataSet, ComputationGraph, boolean) - Method in class org.deeplearning4j.spark.impl.paramavg.ParameterAveragingTrainingWorker
-
- processMinibatchWithStats(DataSet, MultiLayerNetwork, boolean) - Method in class org.deeplearning4j.spark.parameterserver.training.SharedTrainingWorker
-
- processMinibatchWithStats(DataSet, ComputationGraph, boolean) - Method in class org.deeplearning4j.spark.parameterserver.training.SharedTrainingWorker
-
- processMinibatchWithStats(MultiDataSet, ComputationGraph, boolean) - Method in class org.deeplearning4j.spark.parameterserver.training.SharedTrainingWorker
-
- processor(Processor) - Method in class org.deeplearning4j.streaming.routes.CamelKafkaRouteBuilder.Builder
-
- processResults(SparkDl4jMultiLayer, SparkComputationGraph, JavaRDD<ParameterAveragingTrainingResult>, int, int) - Method in class org.deeplearning4j.spark.impl.paramavg.ParameterAveragingTrainingMaster
-
- processResults(SparkDl4jMultiLayer, SparkComputationGraph, JavaRDD<SharedTrainingResult>) - Method in class org.deeplearning4j.spark.parameterserver.training.SharedTrainingMaster
-
- producerAffinity - Variable in class org.deeplearning4j.datasets.iterator.parallel.BaseParallelDataSetIterator
-
- ProgressLog - Class in com.atilika.kuromoji.compile
-
Simple progress logger
- ProgressLog() - Constructor for class com.atilika.kuromoji.compile.ProgressLog
-
- promptPassphrase(String) - Method in class org.deeplearning4j.aws.ec2.provision.HostProvisioner
-
- promptPassword(String) - Method in class org.deeplearning4j.aws.ec2.provision.HostProvisioner
-
- promptYesNo(String) - Method in class org.deeplearning4j.aws.ec2.provision.HostProvisioner
-
- PRONUNCIATION - Static variable in class com.atilika.kuromoji.ipadic.compile.DictionaryEntry
-
- properties - Variable in class org.deeplearning4j.aws.emr.EmrConfig
-
- publish(INDArray[]) - Method in class org.deeplearning4j.streaming.kafka.NDArrayPublisher
-
Publish an ndarray
- publish(INDArray) - Method in class org.deeplearning4j.streaming.kafka.NDArrayPublisher
-
Publish an ndarray
- pullLastTimeSteps(INDArray, INDArray) - Static method in class org.deeplearning4j.util.TimeSeriesUtils
-
Extract out the last time steps (2d array from 3d array input) accounting for the mask layer, if present.
- pullLastTimeSteps(INDArray, INDArray, LayerWorkspaceMgr, ArrayType) - Static method in class org.deeplearning4j.util.TimeSeriesUtils
-
Extract out the last time steps (2d array from 3d array input) accounting for the mask layer, if present.
- put(String, V) - Method in class com.atilika.kuromoji.trie.PatriciaTrie
-
Puts value into trie identifiable by key into this trie (key should be non-null)
- put(String, String) - Static method in class org.ansj.library.AmbiguityLibrary
-
动态添加
- put(String, String, Forest) - Static method in class org.ansj.library.AmbiguityLibrary
-
- put(String, String) - Static method in class org.ansj.library.CrfLibrary
-
动态添加
- put(String, String, SplitWord) - Static method in class org.ansj.library.CrfLibrary
-
- put(String, String, Forest) - Static method in class org.ansj.library.DicLibrary
-
动态添加词典
- put(String, String) - Static method in class org.ansj.library.DicLibrary
-
动态添加词典
- put(String, String, StopRecognition) - Static method in class org.ansj.library.StopLibrary
-
动态添加词典
- put(String, String) - Static method in class org.ansj.library.StopLibrary
-
动态添加词典
- put(String, String) - Static method in class org.ansj.library.SynonymsLibrary
-
动态添加
- put(String, String, SmartForest<List<String>>) - Static method in class org.ansj.library.SynonymsLibrary
-
- put(E) - Method in class org.deeplearning4j.optimize.solvers.accumulation.FancyBlockingQueue
-
- put(T) - Method in class org.deeplearning4j.parallelism.MagicQueue
-
Deprecated.
- putAll(Map<? extends String, ? extends V>) - Method in class com.atilika.kuromoji.trie.PatriciaTrie
-
Inserts all key and value entries in a map into this trie
- putCode(int, INDArray) - Method in class org.deeplearning4j.models.embeddings.inmemory.InMemoryLookupTable
-
- putCode(int, INDArray) - Method in interface org.deeplearning4j.models.embeddings.WeightLookupTable
-
- putCost(short, short, short) - Method in class com.atilika.kuromoji.compile.ConnectionCostsCompiler
-
- putDataSetMetaDataClassName(DirectBuffer, int, int) - Method in class org.deeplearning4j.ui.stats.sbe.UpdateEncoder
-
- putDataSetMetaDataClassName(byte[], int, int) - Method in class org.deeplearning4j.ui.stats.sbe.UpdateEncoder
-
- putDeviceDescription(DirectBuffer, int, int) - Method in class org.deeplearning4j.ui.stats.sbe.StaticInfoEncoder.HwDeviceInfoGroupEncoder
-
- putDeviceDescription(byte[], int, int) - Method in class org.deeplearning4j.ui.stats.sbe.StaticInfoEncoder.HwDeviceInfoGroupEncoder
-
- putEntries(List<BufferEntry>) - Method in class com.atilika.kuromoji.compile.TokenInfoBufferCompiler
-
- putEnvKey(DirectBuffer, int, int) - Method in class org.deeplearning4j.ui.stats.sbe.StaticInfoEncoder.SwEnvironmentInfoEncoder
-
- putEnvKey(byte[], int, int) - Method in class org.deeplearning4j.ui.stats.sbe.StaticInfoEncoder.SwEnvironmentInfoEncoder
-
- putEnvValue(DirectBuffer, int, int) - Method in class org.deeplearning4j.ui.stats.sbe.StaticInfoEncoder.SwEnvironmentInfoEncoder
-
- putEnvValue(byte[], int, int) - Method in class org.deeplearning4j.ui.stats.sbe.StaticInfoEncoder.SwEnvironmentInfoEncoder
-
- putGcName(DirectBuffer, int, int) - Method in class org.deeplearning4j.ui.stats.sbe.UpdateEncoder.GcStatsEncoder
-
- putGcName(byte[], int, int) - Method in class org.deeplearning4j.ui.stats.sbe.UpdateEncoder.GcStatsEncoder
-
- putHwHardwareUID(DirectBuffer, int, int) - Method in class org.deeplearning4j.ui.stats.sbe.StaticInfoEncoder
-
- putHwHardwareUID(byte[], int, int) - Method in class org.deeplearning4j.ui.stats.sbe.StaticInfoEncoder
-
- putIfAbsent(String, String) - Static method in class org.ansj.library.AmbiguityLibrary
-
- putIfAbsent(String, String) - Static method in class org.ansj.library.CrfLibrary
-
- putIfAbsent(String, String) - Static method in class org.ansj.library.DicLibrary
-
动态添加词典
- putIfAbsent(String, String, Forest) - Static method in class org.ansj.library.DicLibrary
-
动态添加词典
- putIfAbsent(String, String) - Static method in class org.ansj.library.StopLibrary
-
动态添加词典
- putIfAbsent(String, String, StopRecognition) - Static method in class org.ansj.library.StopLibrary
-
动态添加词典
- putIfAbsent(String, String) - Static method in class org.ansj.library.SynonymsLibrary
-
- putInitTypeClass(DirectBuffer, int, int) - Method in class org.deeplearning4j.ui.stats.sbe.StorageMetaDataEncoder
-
- putInitTypeClass(byte[], int, int) - Method in class org.deeplearning4j.ui.stats.sbe.StorageMetaDataEncoder
-
- putLayerName(DirectBuffer, int, int) - Method in class org.deeplearning4j.ui.stats.sbe.UpdateEncoder.LayerNamesEncoder
-
- putLayerName(byte[], int, int) - Method in class org.deeplearning4j.ui.stats.sbe.UpdateEncoder.LayerNamesEncoder
-
- putLibrary(String, String, Object) - Static method in class org.ansj.util.MyStaticValue
-
增加一个词典
- putLibrary(String, String) - Static method in class org.ansj.util.MyStaticValue
-
懒加载一个词典
- putMap(TreeMap<Integer, String>) - Method in class com.atilika.kuromoji.buffer.StringValueMapBuffer
-
- putModelConfigClassName(DirectBuffer, int, int) - Method in class org.deeplearning4j.ui.stats.sbe.StaticInfoEncoder
-
- putModelConfigClassName(byte[], int, int) - Method in class org.deeplearning4j.ui.stats.sbe.StaticInfoEncoder
-
- putModelConfigJson(DirectBuffer, int, int) - Method in class org.deeplearning4j.ui.stats.sbe.StaticInfoEncoder
-
- putModelConfigJson(byte[], int, int) - Method in class org.deeplearning4j.ui.stats.sbe.StaticInfoEncoder
-
- putModelParamNames(DirectBuffer, int, int) - Method in class org.deeplearning4j.ui.stats.sbe.StaticInfoEncoder.ModelParamNamesEncoder
-
- putModelParamNames(byte[], int, int) - Method in class org.deeplearning4j.ui.stats.sbe.StaticInfoEncoder.ModelParamNamesEncoder
-
- putParamName(DirectBuffer, int, int) - Method in class org.deeplearning4j.ui.stats.sbe.UpdateEncoder.ParamNamesEncoder
-
- putParamName(byte[], int, int) - Method in class org.deeplearning4j.ui.stats.sbe.UpdateEncoder.ParamNamesEncoder
-
- putSessionID(DirectBuffer, int, int) - Method in class org.deeplearning4j.ui.stats.sbe.StaticInfoEncoder
-
- putSessionID(byte[], int, int) - Method in class org.deeplearning4j.ui.stats.sbe.StaticInfoEncoder
-
- putSessionID(DirectBuffer, int, int) - Method in class org.deeplearning4j.ui.stats.sbe.StorageMetaDataEncoder
-
- putSessionID(byte[], int, int) - Method in class org.deeplearning4j.ui.stats.sbe.StorageMetaDataEncoder
-
- putSessionID(DirectBuffer, int, int) - Method in class org.deeplearning4j.ui.stats.sbe.UpdateEncoder
-
- putSessionID(byte[], int, int) - Method in class org.deeplearning4j.ui.stats.sbe.UpdateEncoder
-
- putStaticInfo(Persistable) - Method in class org.deeplearning4j.api.storage.impl.CollectionStatsStorageRouter
-
- putStaticInfo(Collection<? extends Persistable>) - Method in class org.deeplearning4j.api.storage.impl.CollectionStatsStorageRouter
-
- putStaticInfo(Persistable) - Method in class org.deeplearning4j.api.storage.impl.RemoteUIStatsStorageRouter
-
- putStaticInfo(Collection<? extends Persistable>) - Method in class org.deeplearning4j.api.storage.impl.RemoteUIStatsStorageRouter
-
- putStaticInfo(Persistable) - Method in interface org.deeplearning4j.api.storage.StatsStorageRouter
-
Static info: reported once per session, upon initialization
- putStaticInfo(Collection<? extends Persistable>) - Method in interface org.deeplearning4j.api.storage.StatsStorageRouter
-
Static info: reported once per session, upon initialization
- putStaticInfo(Persistable) - Method in class org.deeplearning4j.spark.impl.listeners.VanillaStatsStorageRouter
-
- putStaticInfo(Collection<? extends Persistable>) - Method in class org.deeplearning4j.spark.impl.listeners.VanillaStatsStorageRouter
-
- putStaticInfo(Persistable) - Method in class org.deeplearning4j.ui.storage.BaseCollectionStatsStorage
-
- putStaticInfo(Collection<? extends Persistable>) - Method in class org.deeplearning4j.ui.storage.BaseCollectionStatsStorage
-
- putStaticInfo(Persistable) - Method in class org.deeplearning4j.ui.storage.InMemoryStatsStorage
-
- putStaticInfo(Persistable) - Method in class org.deeplearning4j.ui.storage.mapdb.MapDBStatsStorage
-
- putStaticInfo(Persistable) - Method in class org.deeplearning4j.ui.storage.sqlite.J7FileStatsStorage
-
- putStaticInfo(Collection<? extends Persistable>) - Method in class org.deeplearning4j.ui.storage.sqlite.J7FileStatsStorage
-
- putStorageMetaData(StorageMetaData) - Method in class org.deeplearning4j.api.storage.impl.CollectionStatsStorageRouter
-
- putStorageMetaData(Collection<? extends StorageMetaData>) - Method in class org.deeplearning4j.api.storage.impl.CollectionStatsStorageRouter
-
- putStorageMetaData(StorageMetaData) - Method in class org.deeplearning4j.api.storage.impl.RemoteUIStatsStorageRouter
-
- putStorageMetaData(Collection<? extends StorageMetaData>) - Method in class org.deeplearning4j.api.storage.impl.RemoteUIStatsStorageRouter
-
- putStorageMetaData(StorageMetaData) - Method in interface org.deeplearning4j.api.storage.StatsStorageRouter
-
Method to store some additional metadata for each session.
- putStorageMetaData(Collection<? extends StorageMetaData>) - Method in interface org.deeplearning4j.api.storage.StatsStorageRouter
-
- putStorageMetaData(StorageMetaData) - Method in class org.deeplearning4j.spark.impl.listeners.VanillaStatsStorageRouter
-
- putStorageMetaData(Collection<? extends StorageMetaData>) - Method in class org.deeplearning4j.spark.impl.listeners.VanillaStatsStorageRouter
-
- putStorageMetaData(StorageMetaData) - Method in class org.deeplearning4j.ui.storage.BaseCollectionStatsStorage
-
- putStorageMetaData(Collection<? extends StorageMetaData>) - Method in class org.deeplearning4j.ui.storage.BaseCollectionStatsStorage
-
- putStorageMetaData(StorageMetaData) - Method in class org.deeplearning4j.ui.storage.InMemoryStatsStorage
-
- putStorageMetaData(StorageMetaData) - Method in class org.deeplearning4j.ui.storage.mapdb.MapDBStatsStorage
-
- putStorageMetaData(StorageMetaData) - Method in class org.deeplearning4j.ui.storage.sqlite.J7FileStatsStorage
-
- putStorageMetaData(Collection<? extends StorageMetaData>) - Method in class org.deeplearning4j.ui.storage.sqlite.J7FileStatsStorage
-
- putSwArch(DirectBuffer, int, int) - Method in class org.deeplearning4j.ui.stats.sbe.StaticInfoEncoder
-
- putSwArch(byte[], int, int) - Method in class org.deeplearning4j.ui.stats.sbe.StaticInfoEncoder
-
- putSwHostName(DirectBuffer, int, int) - Method in class org.deeplearning4j.ui.stats.sbe.StaticInfoEncoder
-
- putSwHostName(byte[], int, int) - Method in class org.deeplearning4j.ui.stats.sbe.StaticInfoEncoder
-
- putSwJvmName(DirectBuffer, int, int) - Method in class org.deeplearning4j.ui.stats.sbe.StaticInfoEncoder
-
- putSwJvmName(byte[], int, int) - Method in class org.deeplearning4j.ui.stats.sbe.StaticInfoEncoder
-
- putSwJvmSpecVersion(DirectBuffer, int, int) - Method in class org.deeplearning4j.ui.stats.sbe.StaticInfoEncoder
-
- putSwJvmSpecVersion(byte[], int, int) - Method in class org.deeplearning4j.ui.stats.sbe.StaticInfoEncoder
-
- putSwJvmUID(DirectBuffer, int, int) - Method in class org.deeplearning4j.ui.stats.sbe.StaticInfoEncoder
-
- putSwJvmUID(byte[], int, int) - Method in class org.deeplearning4j.ui.stats.sbe.StaticInfoEncoder
-
- putSwJvmVersion(DirectBuffer, int, int) - Method in class org.deeplearning4j.ui.stats.sbe.StaticInfoEncoder
-
- putSwJvmVersion(byte[], int, int) - Method in class org.deeplearning4j.ui.stats.sbe.StaticInfoEncoder
-
- putSwNd4jBackendClass(DirectBuffer, int, int) - Method in class org.deeplearning4j.ui.stats.sbe.StaticInfoEncoder
-
- putSwNd4jBackendClass(byte[], int, int) - Method in class org.deeplearning4j.ui.stats.sbe.StaticInfoEncoder
-
- putSwNd4jDataTypeName(DirectBuffer, int, int) - Method in class org.deeplearning4j.ui.stats.sbe.StaticInfoEncoder
-
- putSwNd4jDataTypeName(byte[], int, int) - Method in class org.deeplearning4j.ui.stats.sbe.StaticInfoEncoder
-
- putSwOsName(DirectBuffer, int, int) - Method in class org.deeplearning4j.ui.stats.sbe.StaticInfoEncoder
-
- putSwOsName(byte[], int, int) - Method in class org.deeplearning4j.ui.stats.sbe.StaticInfoEncoder
-
- putTypeID(DirectBuffer, int, int) - Method in class org.deeplearning4j.ui.stats.sbe.StaticInfoEncoder
-
- putTypeID(byte[], int, int) - Method in class org.deeplearning4j.ui.stats.sbe.StaticInfoEncoder
-
- putTypeID(DirectBuffer, int, int) - Method in class org.deeplearning4j.ui.stats.sbe.StorageMetaDataEncoder
-
- putTypeID(byte[], int, int) - Method in class org.deeplearning4j.ui.stats.sbe.StorageMetaDataEncoder
-
- putTypeID(DirectBuffer, int, int) - Method in class org.deeplearning4j.ui.stats.sbe.UpdateEncoder
-
- putTypeID(byte[], int, int) - Method in class org.deeplearning4j.ui.stats.sbe.UpdateEncoder
-
- putUpdate(Persistable) - Method in class org.deeplearning4j.api.storage.impl.CollectionStatsStorageRouter
-
- putUpdate(Collection<? extends Persistable>) - Method in class org.deeplearning4j.api.storage.impl.CollectionStatsStorageRouter
-
- putUpdate(Persistable) - Method in class org.deeplearning4j.api.storage.impl.RemoteUIStatsStorageRouter
-
- putUpdate(Collection<? extends Persistable>) - Method in class org.deeplearning4j.api.storage.impl.RemoteUIStatsStorageRouter
-
- putUpdate(Persistable) - Method in interface org.deeplearning4j.api.storage.StatsStorageRouter
-
Updates: stored multiple times per session (periodically, for example)
- putUpdate(Collection<? extends Persistable>) - Method in interface org.deeplearning4j.api.storage.StatsStorageRouter
-
Updates: stored multiple times per session (periodically, for example)
- putUpdate(Persistable) - Method in class org.deeplearning4j.spark.impl.listeners.VanillaStatsStorageRouter
-
- putUpdate(Collection<? extends Persistable>) - Method in class org.deeplearning4j.spark.impl.listeners.VanillaStatsStorageRouter
-
- putUpdate(Persistable) - Method in class org.deeplearning4j.ui.storage.BaseCollectionStatsStorage
-
- putUpdate(Collection<? extends Persistable>) - Method in class org.deeplearning4j.ui.storage.BaseCollectionStatsStorage
-
- putUpdate(Persistable) - Method in class org.deeplearning4j.ui.storage.InMemoryStatsStorage
-
- putUpdate(Persistable) - Method in class org.deeplearning4j.ui.storage.mapdb.MapDBStatsStorage
-
- putUpdate(Persistable) - Method in class org.deeplearning4j.ui.storage.sqlite.J7FileStatsStorage
-
- putUpdate(Collection<? extends Persistable>) - Method in class org.deeplearning4j.ui.storage.sqlite.J7FileStatsStorage
-
- putUpdateTypeClass(DirectBuffer, int, int) - Method in class org.deeplearning4j.ui.stats.sbe.StorageMetaDataEncoder
-
- putUpdateTypeClass(byte[], int, int) - Method in class org.deeplearning4j.ui.stats.sbe.StorageMetaDataEncoder
-
- putVector(String, INDArray) - Method in class org.deeplearning4j.models.embeddings.inmemory.InMemoryLookupTable
-
Inserts a word vector
- putVector(String, INDArray) - Method in interface org.deeplearning4j.models.embeddings.WeightLookupTable
-
Inserts a word vector
- putVocabWord(String) - Method in class org.deeplearning4j.models.word2vec.wordstore.inmemory.AbstractCache
-
Deprecated.
- putVocabWord(String) - Method in class org.deeplearning4j.models.word2vec.wordstore.inmemory.InMemoryLookupCache
-
Deprecated.
- putVocabWord(String) - Method in interface org.deeplearning4j.models.word2vec.wordstore.VocabCache
-
Deprecated.
- putWorkerID(DirectBuffer, int, int) - Method in class org.deeplearning4j.ui.stats.sbe.StaticInfoEncoder
-
- putWorkerID(byte[], int, int) - Method in class org.deeplearning4j.ui.stats.sbe.StaticInfoEncoder
-
- putWorkerID(DirectBuffer, int, int) - Method in class org.deeplearning4j.ui.stats.sbe.StorageMetaDataEncoder
-
- putWorkerID(byte[], int, int) - Method in class org.deeplearning4j.ui.stats.sbe.StorageMetaDataEncoder
-
- putWorkerID(DirectBuffer, int, int) - Method in class org.deeplearning4j.ui.stats.sbe.UpdateEncoder
-
- putWorkerID(byte[], int, int) - Method in class org.deeplearning4j.ui.stats.sbe.UpdateEncoder
-
- PXZ_B - Static variable in class org.deeplearning4j.nn.params.VariationalAutoencoderParamInitializer
-
Key for bias parameters connecting the last decoder layer and p(data|z) (according to whatever
ReconstructionDistribution is set for the VAE)
- PXZ_PREFIX - Static variable in class org.deeplearning4j.nn.params.VariationalAutoencoderParamInitializer
-
- PXZ_W - Static variable in class org.deeplearning4j.nn.params.VariationalAutoencoderParamInitializer
-
Key for weight parameters connecting the last decoder layer and p(data|z) (according to whatever
ReconstructionDistribution is set for the VAE)
- PZX_LOGSTD2_B - Static variable in class org.deeplearning4j.nn.params.VariationalAutoencoderParamInitializer
-
Key for bias parameters for log(sigma^2) in p(z|data)
- PZX_LOGSTD2_PREFIX - Static variable in class org.deeplearning4j.nn.params.VariationalAutoencoderParamInitializer
-
- PZX_LOGSTD2_W - Static variable in class org.deeplearning4j.nn.params.VariationalAutoencoderParamInitializer
-
Key for weight parameters connecting the last encoder layer and the log(sigma^2) values for p(z|data)
- PZX_MEAN_B - Static variable in class org.deeplearning4j.nn.params.VariationalAutoencoderParamInitializer
-
Key for bias parameters for the mean values for p(z|data)
- PZX_MEAN_PREFIX - Static variable in class org.deeplearning4j.nn.params.VariationalAutoencoderParamInitializer
-
- PZX_MEAN_W - Static variable in class org.deeplearning4j.nn.params.VariationalAutoencoderParamInitializer
-
Key for weight parameters connecting the last encoder layer and the mean values for p(z|data)
- PZX_PREFIX - Static variable in class org.deeplearning4j.nn.params.VariationalAutoencoderParamInitializer
-
- pzxActivationFn(IActivation) - Method in class org.deeplearning4j.nn.conf.layers.variational.VariationalAutoencoder.Builder
-
Activation function for the input to P(z|data).
Care should be taken with this, as some activation functions (relu, etc) are not suitable due to being
bounded in range [0,infinity).
- pzxActivationFn - Variable in class org.deeplearning4j.nn.layers.variational.VariationalAutoencoder
-
- pzxActivationFunction(Activation) - Method in class org.deeplearning4j.nn.conf.layers.variational.VariationalAutoencoder.Builder
-
Activation function for the input to P(z|data).
Care should be taken with this, as some activation functions (relu, etc) are not suitable due to being
bounded in range [0,infinity).
- R_KEY - Static variable in class org.deeplearning4j.nn.layers.ocnn.OCNNParamInitializer
-
- randomDoubleBetween(double, double) - Static method in class org.deeplearning4j.clustering.util.MathUtils
-
- randomFloatBetween(float, float) - Static method in class org.deeplearning4j.clustering.util.MathUtils
-
- randomNumberBetween(double, double) - Static method in class org.deeplearning4j.clustering.util.MathUtils
-
Generates a random integer between the specified numbers
- randomNumberBetween(double, double, RandomGenerator) - Static method in class org.deeplearning4j.clustering.util.MathUtils
-
Generates a random integer between the specified numbers
- randomNumberBetween(double, double, Random) - Static method in class org.deeplearning4j.clustering.util.MathUtils
-
Generates a random integer between the specified numbers
- RandomProjectionLSH - Class in org.deeplearning4j.clustering.lsh
-
This class implements Entropy LSH for the cosine distance, in order to preserve memory for large datasets.
- RandomProjectionLSH(int, int, int, double) - Constructor for class org.deeplearning4j.clustering.lsh.RandomProjectionLSH
-
- RandomProjectionLSH(int, int, int, double, Random) - Constructor for class org.deeplearning4j.clustering.lsh.RandomProjectionLSH
-
Creates a locality-sensitive hashing index for the cosine distance,
a (d1, d2, (180 − d1)/180,(180 − d2)/180)-sensitive hash family before amplification
- RandomUtils - Class in org.deeplearning4j.models.embeddings.learning.impl.elements
-
RandomUtils is a wrapper that supports all possible
Random methods via the
Math.random()
method and its system-wide
Random object.
- RandomUtils() - Constructor for class org.deeplearning4j.models.embeddings.learning.impl.elements.RandomUtils
-
- RandomWalker<T extends SequenceElement> - Class in org.deeplearning4j.models.sequencevectors.graph.walkers.impl
-
This is Random-based walker for SequenceVectors-based DeepWalk implementation
Original DeepWalk paper: http://arxiv.org/pdf/1403.6652v2
- RandomWalker() - Constructor for class org.deeplearning4j.models.sequencevectors.graph.walkers.impl.RandomWalker
-
- RandomWalker.Builder<T extends SequenceElement> - Class in org.deeplearning4j.models.sequencevectors.graph.walkers.impl
-
- RandomWalkGraphIteratorProvider<V> - Class in org.deeplearning4j.graph.iterator.parallel
-
Random walk graph iterator provider: given a graph, split up the generation of random walks
for parallel learning.
- RandomWalkGraphIteratorProvider(IGraph<V, ?>, int) - Constructor for class org.deeplearning4j.graph.iterator.parallel.RandomWalkGraphIteratorProvider
-
- RandomWalkGraphIteratorProvider(IGraph<V, ?>, int, long, NoEdgeHandling) - Constructor for class org.deeplearning4j.graph.iterator.parallel.RandomWalkGraphIteratorProvider
-
- RandomWalkIterator<V> - Class in org.deeplearning4j.graph.iterator
-
Given a graph, iterate through random walks on that graph of a specified length.
- RandomWalkIterator(IGraph<V, ?>, int) - Constructor for class org.deeplearning4j.graph.iterator.RandomWalkIterator
-
- RandomWalkIterator(IGraph<V, ?>, int, long) - Constructor for class org.deeplearning4j.graph.iterator.RandomWalkIterator
-
Construct a RandomWalkIterator for a given graph, with a specified walk length and random number generator seed.
Uses NoEdgeHandling.EXCEPTION_ON_DISCONNECTED - hence exception will be thrown when generating random
walks on graphs with vertices containing having no edges, or no outgoing edges (for directed graphs)
- RandomWalkIterator(IGraph<V, ?>, int, long, NoEdgeHandling) - Constructor for class org.deeplearning4j.graph.iterator.RandomWalkIterator
-
- RandomWalkIterator(IGraph<V, ?>, int, long, NoEdgeHandling, int, int) - Constructor for class org.deeplearning4j.graph.iterator.RandomWalkIterator
-
Constructor used to generate random walks starting at a subset of the vertices in the graph.
- RankClassificationResult - Class in org.deeplearning4j.nn.simple.multiclass
-
- RankClassificationResult(INDArray) - Constructor for class org.deeplearning4j.nn.simple.multiclass.RankClassificationResult
-
Takes in just a classification matrix
and initializes the labels to just be indices
- RankClassificationResult(INDArray, List<String>) - Constructor for class org.deeplearning4j.nn.simple.multiclass.RankClassificationResult
-
Takes in a classification matrix
and the labels for each column
- ratio - Variable in class org.deeplearning4j.datasets.iterator.DataSetIteratorSplitter
-
- ratio - Variable in class org.deeplearning4j.datasets.iterator.MultiDataSetIteratorSplitter
-
- RawMnistDataSetIterator - Class in org.deeplearning4j.datasets.iterator.impl
-
Mnist data with scaled pixels
- RawMnistDataSetIterator(int, int) - Constructor for class org.deeplearning4j.datasets.iterator.impl.RawMnistDataSetIterator
-
- rddDataSetNumExamples - Variable in class org.deeplearning4j.spark.impl.paramavg.ParameterAveragingTrainingMaster.Builder
-
- rddDataSetNumExamples - Variable in class org.deeplearning4j.spark.impl.paramavg.ParameterAveragingTrainingMaster
-
- rddDataSetNumExamples - Variable in class org.deeplearning4j.spark.parameterserver.training.SharedTrainingMaster
-
- RDDMiniBatches - Class in org.deeplearning4j.spark.datavec
-
RDD mini batch partitioning
- RDDMiniBatches(int, JavaRDD<DataSet>) - Constructor for class org.deeplearning4j.spark.datavec.RDDMiniBatches
-
- RDDMiniBatches.MiniBatchFunction - Class in org.deeplearning4j.spark.datavec
-
- RDDTrainingApproach - Enum in org.deeplearning4j.spark.api
-
Approach to use when training from a JavaRDD<DataSet> or JavaRDD<MultiDataSet>.
- rddTrainingApproach - Variable in class org.deeplearning4j.spark.impl.paramavg.BaseTrainingMaster
-
- rddTrainingApproach - Variable in class org.deeplearning4j.spark.impl.paramavg.ParameterAveragingTrainingMaster.Builder
-
- rddTrainingApproach(RDDTrainingApproach) - Method in class org.deeplearning4j.spark.impl.paramavg.ParameterAveragingTrainingMaster.Builder
-
The approach to use when training on a RDD<DataSet> or RDD<MultiDataSet>.
- rddTrainingApproach - Variable in class org.deeplearning4j.spark.parameterserver.training.SharedTrainingMaster.Builder
-
- rddTrainingApproach(RDDTrainingApproach) - Method in class org.deeplearning4j.spark.parameterserver.training.SharedTrainingMaster.Builder
-
The approach to use when training on a RDD<DataSet> or RDD<MultiDataSet>.
- rddTrainingApproach - Variable in class org.deeplearning4j.spark.parameterserver.training.SharedTrainingMaster
-
- read(InputStream) - Method in class com.atilika.kuromoji.dict.UserDictionary
-
- read(InputStream) - Static method in class com.atilika.kuromoji.io.ByteBufferIO
-
- read(InputStream) - Static method in class com.atilika.kuromoji.trie.DoubleArrayTrie
-
Load Stored data
- read(char[], int, int) - Method in class org.ansj.util.AnsjReader
-
为了功能的单一性我还是不实现了
- readArray(InputStream) - Static method in class com.atilika.kuromoji.io.IntegerArrayIO
-
- readArray(InputStream) - Static method in class com.atilika.kuromoji.io.StringArrayIO
-
- readArray2D(InputStream) - Static method in class com.atilika.kuromoji.io.IntegerArrayIO
-
- readArray2D(InputStream) - Static method in class com.atilika.kuromoji.io.StringArrayIO
-
- readAttributeAsFixedLengthString(String, int) - Method in class org.deeplearning4j.nn.modelimport.keras.Hdf5Archive
-
Read string attribute from group path.
- readAttributeAsJson(String, String...) - Method in class org.deeplearning4j.nn.modelimport.keras.Hdf5Archive
-
Read JSON-formatted string attribute from group path.
- readAttributeAsString(String, String...) - Method in class org.deeplearning4j.nn.modelimport.keras.Hdf5Archive
-
Read string attribute from group path.
- readCharacterDefinition(InputStream, String) - Method in class com.atilika.kuromoji.compile.CharacterDefinitionsCompiler
-
- readCosts(InputStream) - Method in class com.atilika.kuromoji.compile.ConnectionCostsCompiler
-
- readDataSet(String, String...) - Method in class org.deeplearning4j.nn.modelimport.keras.Hdf5Archive
-
Read data set as ND4J array from group path.
- reader - Variable in class org.deeplearning4j.text.sentenceiterator.UimaSentenceIterator
-
- readFloat(InputStream) - Static method in class org.deeplearning4j.models.embeddings.loader.WordVectorSerializer
-
Read a float from a data input stream Credit to:
https://github.com/NLPchina/Word2VEC_java/blob/master/src/com/ansj/vec/Word2VEC.java
- readImage() - Method in class org.deeplearning4j.datasets.mnist.MnistImageFile
-
Reads the image at the current position.
- readImage() - Method in class org.deeplearning4j.datasets.mnist.MnistManager
-
Reads the current image.
- readImagesUnsafe(int) - Method in class org.deeplearning4j.datasets.mnist.MnistImageFile
-
Read the specified number of images from the current position, to a byte[nImages][rows*cols]
Note that MNIST data set is stored as unsigned bytes; this method returns signed bytes without conversion
(i.e., same bits, but requires conversion before use)
- readImageUnsafe(int) - Method in class org.deeplearning4j.datasets.mnist.MnistManager
-
- READING - Static variable in class com.atilika.kuromoji.ipadic.compile.DictionaryEntry
-
- READING_FEATURE - Static variable in class com.atilika.kuromoji.ipadic.compile.DictionaryEntry
-
- readingFeature - Variable in class com.atilika.kuromoji.TokenizerBase.Builder
-
- readLabel() - Method in class org.deeplearning4j.datasets.mnist.MnistLabelFile
-
Reads the integer at the current position.
- readLabel() - Method in class org.deeplearning4j.datasets.mnist.MnistManager
-
Reads the current label.
- readLabel(int) - Method in class org.deeplearning4j.datasets.mnist.MnistManager
-
- readLabels(int) - Method in class org.deeplearning4j.datasets.mnist.MnistLabelFile
-
Read the specified number of labels from the current position
- readLine() - Method in class org.ansj.util.AnsjReader
-
读取一行数据。ps 读取结果会忽略 \n \r
- readObjectFromFile(String, Class<T>, JavaSparkContext) - Static method in class org.deeplearning4j.spark.util.SparkUtils
-
Read an object from HDFS (or local) using default Java object serialization
- readObjectFromFile(String, Class<T>, SparkContext) - Static method in class org.deeplearning4j.spark.util.SparkUtils
-
Read an object from HDFS (or local) using default Java object serialization
- readOnly - Variable in class org.deeplearning4j.models.sequencevectors.transformers.impl.SentenceTransformer.Builder
-
- readOnly(boolean) - Method in class org.deeplearning4j.models.sequencevectors.transformers.impl.SentenceTransformer.Builder
-
- readOnly - Variable in class org.deeplearning4j.models.sequencevectors.transformers.impl.SentenceTransformer
-
- readParagraphVectors(String) - Static method in class org.deeplearning4j.models.embeddings.loader.WordVectorSerializer
-
This method restores ParagraphVectors model previously saved with writeParagraphVectors()
- readParagraphVectors(File) - Static method in class org.deeplearning4j.models.embeddings.loader.WordVectorSerializer
-
This method restores ParagraphVectors model previously saved with writeParagraphVectors()
- readParagraphVectors(InputStream) - Static method in class org.deeplearning4j.models.embeddings.loader.WordVectorSerializer
-
This method restores ParagraphVectors model previously saved with writeParagraphVectors()
- readParagraphVectorsFromText(String) - Static method in class org.deeplearning4j.models.embeddings.loader.WordVectorSerializer
-
Deprecated.
- readParagraphVectorsFromText(File) - Static method in class org.deeplearning4j.models.embeddings.loader.WordVectorSerializer
-
Deprecated.
- readParagraphVectorsFromText(InputStream) - Static method in class org.deeplearning4j.models.embeddings.loader.WordVectorSerializer
-
Deprecated.
- readSequenceVectors(SequenceElementFactory<T>, File) - Static method in class org.deeplearning4j.models.embeddings.loader.WordVectorSerializer
-
This method loads previously saved SequenceVectors model from File
- readSequenceVectors(SequenceElementFactory<T>, InputStream) - Static method in class org.deeplearning4j.models.embeddings.loader.WordVectorSerializer
-
This method loads previously saved SequenceVectors model from InputStream
- readSparseArray2D(InputStream) - Static method in class com.atilika.kuromoji.io.IntegerArrayIO
-
- readSparseArray2D(InputStream) - Static method in class com.atilika.kuromoji.io.StringArrayIO
-
- readStream(InputStream) - Method in class org.deeplearning4j.text.documentiterator.interoperability.DocumentIteratorConverter
-
- readString(DataInputStream) - Static method in class org.deeplearning4j.models.embeddings.loader.WordVectorSerializer
-
Read a string from a data input stream Credit to:
https://github.com/NLPchina/Word2VEC_java/blob/master/src/com/ansj/vec/Word2VEC.java
- readStringFromFile(String, JavaSparkContext) - Static method in class org.deeplearning4j.spark.util.SparkUtils
-
Read a UTF-8 format String from HDFS (or local)
- readStringFromFile(String, SparkContext) - Static method in class org.deeplearning4j.spark.util.SparkUtils
-
Read a UTF-8 format String from HDFS (or local)
- readTokenInfo(InputStream) - Method in class com.atilika.kuromoji.compile.TokenInfoDictionaryCompilerBase
-
- readUnknownDefinition(InputStream, String) - Method in class com.atilika.kuromoji.compile.UnknownDictionaryCompiler
-
- readVocabCache(File) - Static method in class org.deeplearning4j.models.embeddings.loader.WordVectorSerializer
-
This method reads vocab cache from provided file.
- readVocabCache(InputStream) - Static method in class org.deeplearning4j.models.embeddings.loader.WordVectorSerializer
-
This method reads vocab cache from provided InputStream.
- readWord2Vec(File) - Static method in class org.deeplearning4j.models.embeddings.loader.WordVectorSerializer
-
Deprecated.
- readWord2VecFromText(File, File, File, File, VectorsConfiguration) - Static method in class org.deeplearning4j.models.embeddings.loader.WordVectorSerializer
-
This method allows you to read ParagraphVectors from externally originated vectors and syn1.
- readWord2VecModel(File) - Static method in class org.deeplearning4j.models.embeddings.loader.WordVectorSerializer
-
This method
1) Binary model, either compressed or not.
- readWord2VecModel(String) - Static method in class org.deeplearning4j.models.embeddings.loader.WordVectorSerializer
-
This method
1) Binary model, either compressed or not.
- readWord2VecModel(String, boolean) - Static method in class org.deeplearning4j.models.embeddings.loader.WordVectorSerializer
-
This method
1) Binary model, either compressed or not.
- readWord2VecModel(File, boolean) - Static method in class org.deeplearning4j.models.embeddings.loader.WordVectorSerializer
-
This method
1) Binary model, either compressed or not.
- realMin - Variable in class org.deeplearning4j.plot.BarnesHutTsne
-
- realMin - Variable in class org.deeplearning4j.plot.Tsne.Builder
-
- realMin - Variable in class org.deeplearning4j.plot.Tsne
-
- realStr - Variable in class org.ansj.util.Graph
-
- rearrange() - Method in class org.deeplearning4j.datasets.rearrange.LocalUnstructuredDataFormatter
-
- reassignExistingModel() - Method in class org.deeplearning4j.models.paragraphvectors.ParagraphVectors
-
- recall(int) - Method in class org.deeplearning4j.eval.Evaluation
-
Returns the recall for a given label
- recall(int, double) - Method in class org.deeplearning4j.eval.Evaluation
-
Returns the recall for a given label
- recall() - Method in class org.deeplearning4j.eval.Evaluation
-
Recall based on guesses so far
Note: value returned will differ depending on number of classes and settings.
1.
- recall(EvaluationAveraging) - Method in class org.deeplearning4j.eval.Evaluation
-
Calculate the average recall for all classes - can specify whether macro or micro averaging should be used
NOTE: if any classes have tp=0 and fn=0, (recall=0/0) these are excluded from the average
- recall(int) - Method in class org.deeplearning4j.eval.EvaluationBinary
-
Get the recall (tp / (tp + fn)) for the specified output
- recall(long, long, double) - Static method in class org.deeplearning4j.eval.EvaluationUtils
-
Calculate the recall from true positive and false negative counts
- receiveUpdate(INDArray) - Method in class org.deeplearning4j.optimize.solvers.accumulation.BasicGradientsAccumulator
-
This method accepts updates suitable for StepFunction and puts them to the queue, which is used in backpropagation loop
PLEASE NOTE: array is expected to be ready for use and match params dimensionality
- receiveUpdate(INDArray) - Method in class org.deeplearning4j.optimize.solvers.accumulation.EncodedGradientsAccumulator
-
This method accepts updates suitable for StepFunction and puts them to the queue, which is used in backpropagation loop
- receiveUpdate(INDArray) - Method in interface org.deeplearning4j.optimize.solvers.accumulation.GradientsAccumulator
-
This method accepts updates suitable for StepFunction and puts them to the queue, which is used in backpropagation loop
PLEASE NOTE: array is expected to be ready for use and match params dimensionality
- recognition(Recognition) - Method in class org.ansj.domain.Result
-
调用一个发现引擎
- recognition(Term[]) - Method in class org.ansj.recognition.arrimpl.AsianPersonRecognition
-
- recognition(Term[]) - Method in class org.ansj.recognition.arrimpl.ForeignPersonRecognition
-
- recognition(Term[]) - Method in class org.ansj.recognition.arrimpl.NewWordRecognition
-
- recognition(Term[]) - Method in class org.ansj.recognition.arrimpl.NumRecognition
-
数字+数字合并,zheng
- recognition(Term[]) - Method in class org.ansj.recognition.arrimpl.UserDefineRecognition
-
- recognition(Result) - Method in class org.ansj.recognition.impl.BookRecognition
-
- recognition(Result) - Method in class org.ansj.recognition.impl.DicRecognition
-
- recognition(Result) - Method in class org.ansj.recognition.impl.EmailRecognition
-
- recognition(Result) - Method in class org.ansj.recognition.impl.IDCardRecognition
-
- recognition(Result) - Method in class org.ansj.recognition.impl.NatureRecognition
-
进行最佳词性查找,引用赋值.所以不需要有返回值
- recognition(List<String>) - Method in class org.ansj.recognition.impl.NatureRecognition
-
传入一组。词对词语进行。词性标注
- recognition(List<String>, int) - Method in class org.ansj.recognition.impl.NatureRecognition
-
传入一组。词对词语进行。词性标注
- recognition(Result) - Method in class org.ansj.recognition.impl.StopRecognition
-
- recognition(Result) - Method in class org.ansj.recognition.impl.SynonymsRecgnition
-
- recognition(Result) - Method in class org.ansj.recognition.impl.TimeRecognition
-
- recognition(Result) - Method in class org.ansj.recognition.impl.UserDicNatureRecognition
-
- Recognition - Interface in org.ansj.recognition
-
词语结果识别接口,用来通过规则方式识别词语,对结果的二次加工
- recognition(Result) - Method in interface org.ansj.recognition.Recognition
-
- recognition(Term[]) - Method in interface org.ansj.recognition.TermArrRecognition
-
- reconstruct(INDArray, int) - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
-
Reconstructs the input.
- ReconstructionDataSetIterator - Class in org.deeplearning4j.datasets.iterator
-
Wraps a data applyTransformToDestination iterator setting the first (feature matrix) as
the labels.
- ReconstructionDataSetIterator(DataSetIterator) - Constructor for class org.deeplearning4j.datasets.iterator.ReconstructionDataSetIterator
-
- ReconstructionDistribution - Interface in org.deeplearning4j.nn.conf.layers.variational
-
The ReconstructionDistribution is used with variational autoencoders
VariationalAutoencoder
to specify the form of the distribution p(data|x).
- reconstructionDistribution(ReconstructionDistribution) - Method in class org.deeplearning4j.nn.conf.layers.variational.VariationalAutoencoder.Builder
-
The reconstruction distribution for the data given the hidden state - i.e., P(data|Z).
This should be selected carefully based on the type of data being modelled.
- reconstructionDistribution - Variable in class org.deeplearning4j.nn.layers.variational.VariationalAutoencoder
-
- reconstructionError(INDArray) - Method in class org.deeplearning4j.nn.layers.variational.VariationalAutoencoder
-
- reconstructionLogProbability(INDArray, int) - Method in class org.deeplearning4j.nn.layers.variational.VariationalAutoencoder
-
- reconstructionProbability(INDArray, int) - Method in class org.deeplearning4j.nn.layers.variational.VariationalAutoencoder
-
Calculate the reconstruction probability, as described in An & Cho, 2015 - "Variational Autoencoder based
Anomaly Detection using Reconstruction Probability" (Algorithm 4)
The authors describe it as follows: "This is essentially the probability of the data being generated from a given
latent variable drawn from the approximate posterior distribution."
Specifically, for each example x in the input, calculate p(x).
- reconstructionProbNumSamples - Variable in class org.deeplearning4j.earlystopping.scorecalc.VAEReconProbScoreCalculator
-
- Record - Class in org.deeplearning4j
-
Created by agibsonccc on 6/7/16.
- Record() - Constructor for class org.deeplearning4j.Record
-
- record(URI, DataInputStream) - Method in class org.deeplearning4j.spark.datavec.iterator.SparkSourceDummyReader
-
- recordReader - Variable in class org.deeplearning4j.datasets.datavec.RecordReaderDataSetIterator.Builder
-
- recordReader - Variable in class org.deeplearning4j.datasets.datavec.RecordReaderDataSetIterator
-
- RecordReaderDataSetIterator - Class in org.deeplearning4j.datasets.datavec
-
Record reader dataset iterator.
- RecordReaderDataSetIterator(RecordReader, int) - Constructor for class org.deeplearning4j.datasets.datavec.RecordReaderDataSetIterator
-
Constructor for classification, where:
(a) the label index is assumed to be the very last Writable/column, and
(b) the number of classes is inferred from RecordReader.getLabels()
Note that if RecordReader.getLabels() returns null, no output labels will be produced
- RecordReaderDataSetIterator(RecordReader, int, int, int) - Constructor for class org.deeplearning4j.datasets.datavec.RecordReaderDataSetIterator
-
Main constructor for classification.
- RecordReaderDataSetIterator(RecordReader, int, int, int, int) - Constructor for class org.deeplearning4j.datasets.datavec.RecordReaderDataSetIterator
-
Constructor for classification, where the maximum number of returned batches is limited to the specified value
- RecordReaderDataSetIterator(RecordReader, int, int, int, boolean) - Constructor for class org.deeplearning4j.datasets.datavec.RecordReaderDataSetIterator
-
Main constructor for multi-label regression (i.e., regression with multiple outputs)
- RecordReaderDataSetIterator(RecordReader, WritableConverter, int, int, int, int, int, boolean) - Constructor for class org.deeplearning4j.datasets.datavec.RecordReaderDataSetIterator
-
Main constructor
- RecordReaderDataSetIterator(RecordReaderDataSetIterator.Builder) - Constructor for class org.deeplearning4j.datasets.datavec.RecordReaderDataSetIterator
-
- RecordReaderDataSetIterator.Builder - Class in org.deeplearning4j.datasets.datavec
-
Builder class for RecordReaderDataSetIterator
- RecordReaderFunction - Class in org.deeplearning4j.spark.datavec
-
Turn a string in to a dataset based on
a record reader
- RecordReaderFunction(RecordReader, int, int, WritableConverter) - Constructor for class org.deeplearning4j.spark.datavec.RecordReaderFunction
-
- RecordReaderFunction(RecordReader, int, int) - Constructor for class org.deeplearning4j.spark.datavec.RecordReaderFunction
-
- RecordReaderMultiDataSetIterator - Class in org.deeplearning4j.datasets.datavec
-
RecordReaderMultiDataSetIterator: A MultiDataSetIterator for data from one or more RecordReaders and SequenceRecordReaders
The idea: generate multiple inputs and multiple outputs from one or more Sequence/RecordReaders.
- RecordReaderMultiDataSetIterator.AlignmentMode - Enum in org.deeplearning4j.datasets.datavec
-
When dealing with time series data of different lengths, how should we align the input/labels time series?
For equal length: use EQUAL_LENGTH
For sequence classification: use ALIGN_END
- RecordReaderMultiDataSetIterator.Builder - Class in org.deeplearning4j.datasets.datavec
-
- RecordToDataSet - Interface in org.deeplearning4j.streaming.conversion.dataset
-
Converts a list of records in to a dataset.
- RecordToNDArray - Interface in org.deeplearning4j.streaming.conversion.ndarray
-
A function convert from record to ndarrays
- recurrent(int) - Static method in class org.deeplearning4j.nn.conf.inputs.InputType
-
InputType for recurrent neural network (time series) data
- recurrent(int, int) - Static method in class org.deeplearning4j.nn.conf.inputs.InputType
-
InputType for recurrent neural network (time series) data
- recurrent(int) - Method in class org.deeplearning4j.nn.conf.NeuralNetConfiguration.ListBuilder.InputTypeBuilder
-
- RECURRENT_WEIGHT_KEY - Static variable in class org.deeplearning4j.nn.params.GravesLSTMParamInitializer
-
Weights for previous time step -> current time step connections
- RECURRENT_WEIGHT_KEY - Static variable in class org.deeplearning4j.nn.params.LSTMParamInitializer
-
Weights for previous time step -> current time step connections
- RECURRENT_WEIGHT_KEY - Static variable in class org.deeplearning4j.nn.params.SimpleRnnParamInitializer
-
- RECURRENT_WEIGHT_KEY_BACKWARDS - Static variable in class org.deeplearning4j.nn.params.GravesBidirectionalLSTMParamInitializer
-
- RECURRENT_WEIGHT_KEY_FORWARDS - Static variable in class org.deeplearning4j.nn.params.GravesBidirectionalLSTMParamInitializer
-
Weights for previous time step -> current time step connections
- recurrentConstraints - Variable in class org.deeplearning4j.nn.conf.layers.BaseRecurrentLayer.Builder
-
- RecurrentLayer - Interface in org.deeplearning4j.nn.api.layers
-
Created by Alex on 28/08/2016.
- ReduceSentenceCount - Class in org.deeplearning4j.spark.text.functions
-
- ReduceSentenceCount() - Constructor for class org.deeplearning4j.spark.text.functions.ReduceSentenceCount
-
- reductionA(ComputationGraphConfiguration.GraphBuilder, int, String, String, String) - Static method in class org.deeplearning4j.zoo.model.helper.NASNetHelper
-
- refreshClusterCenter(Cluster, ClusterInfo) - Static method in class org.deeplearning4j.clustering.cluster.ClusterUtils
-
- refreshClustersCenters(ClusterSet, ClusterSetInfo, ExecutorService) - Static method in class org.deeplearning4j.clustering.cluster.ClusterUtils
-
- Registerable - Interface in org.deeplearning4j.optimize.solvers.accumulation
-
- registerConsumers(int) - Method in class org.deeplearning4j.optimize.solvers.accumulation.EncodedGradientsAccumulator
-
- registerConsumers(int) - Method in class org.deeplearning4j.optimize.solvers.accumulation.FancyBlockingQueue
-
- registerConsumers(int) - Method in interface org.deeplearning4j.optimize.solvers.accumulation.Registerable
-
This method notifies producer about number of consumers for the current consumption cycle
- registerCustomLayer(String, Class<? extends KerasLayer>) - Static method in class org.deeplearning4j.nn.modelimport.keras.KerasLayer
-
Register a custom layer
- registered - Variable in class org.deeplearning4j.optimize.solvers.accumulation.EncodedGradientsAccumulator
-
- registerLegacyClassDefaultName(Class<? extends GraphVertex>) - Static method in class org.deeplearning4j.nn.conf.serde.legacyformat.LegacyGraphVertexDeserializer
-
- registerLegacyClassDefaultName(Class<? extends Layer>) - Static method in class org.deeplearning4j.nn.conf.serde.legacyformat.LegacyLayerDeserializer
-
- registerLegacyClassDefaultName(Class<? extends InputPreProcessor>) - Static method in class org.deeplearning4j.nn.conf.serde.legacyformat.LegacyPreprocessorDeserializer
-
- registerLegacyClassDefaultName(Class<? extends ReconstructionDistribution>) - Static method in class org.deeplearning4j.nn.conf.serde.legacyformat.LegacyReconstructionDistributionDeserializer
-
- registerLegacyClassSpecifiedName(String, Class<? extends GraphVertex>) - Static method in class org.deeplearning4j.nn.conf.serde.legacyformat.LegacyGraphVertexDeserializer
-
- registerLegacyClassSpecifiedName(String, Class<? extends Layer>) - Static method in class org.deeplearning4j.nn.conf.serde.legacyformat.LegacyLayerDeserializer
-
- registerLegacyClassSpecifiedName(String, Class<? extends InputPreProcessor>) - Static method in class org.deeplearning4j.nn.conf.serde.legacyformat.LegacyPreprocessorDeserializer
-
- registerLegacyClassSpecifiedName(String, Class<? extends ReconstructionDistribution>) - Static method in class org.deeplearning4j.nn.conf.serde.legacyformat.LegacyReconstructionDistributionDeserializer
-
- registerLegacyCustomClassesForJSON(Class<?>...) - Static method in class org.deeplearning4j.nn.conf.NeuralNetConfiguration
-
Register a set of classes (Layer, GraphVertex, InputPreProcessor, IActivation, ILossFunction, ReconstructionDistribution
ONLY) for JSON deserialization.
This is required ONLY when BOTH of the following conditions are met:
1.
- registerLegacyCustomClassesForJSON(List<Pair<String, Class>>) - Static method in class org.deeplearning4j.nn.conf.NeuralNetConfiguration
-
Register a set of classes (Layer, GraphVertex, InputPreProcessor, IActivation, ILossFunction, ReconstructionDistribution
ONLY) for JSON deserialization, with custom names.
Using this method directly should never be required (instead: use
NeuralNetConfiguration.registerLegacyCustomClassesForJSON(Class[])
but is added in case it is required in non-standard circumstances.
- registerLegacyCustomClassesForJSONList(List<Class<?>>) - Static method in class org.deeplearning4j.nn.conf.NeuralNetConfiguration
-
- registerStatsStorageListener(StatsStorageListener) - Method in interface org.deeplearning4j.api.storage.StatsStorage
-
Add a new StatsStorageListener.
- registerStatsStorageListener(StatsStorageListener) - Method in class org.deeplearning4j.ui.storage.BaseCollectionStatsStorage
-
- registerStatsStorageListener(StatsStorageListener) - Method in class org.deeplearning4j.ui.storage.sqlite.J7FileStatsStorage
-
- regression - Variable in class org.deeplearning4j.datasets.datavec.RecordReaderDataSetIterator.Builder
-
- regression(int) - Method in class org.deeplearning4j.datasets.datavec.RecordReaderDataSetIterator.Builder
-
Use this for single output regression (i.e., 1 output/regression target)
- regression(int, int) - Method in class org.deeplearning4j.datasets.datavec.RecordReaderDataSetIterator.Builder
-
Use this for multiple output regression (1 or more output/regression targets).
- regression - Variable in class org.deeplearning4j.datasets.datavec.RecordReaderDataSetIterator
-
- RegressionEvaluation - Class in org.deeplearning4j.eval
-
Evaluation method for the evaluation of regression algorithms.
Provides the following metrics, for each column:
- MSE: mean squared error
- MAE: mean absolute error
- RMSE: root mean squared error
- RSE: relative squared error
- PC: pearson correlation coefficient
- R^2: coefficient of determination
See for example: http://www.saedsayad.com/model_evaluation_r.htm
For classification, see
Evaluation
- RegressionEvaluation() - Constructor for class org.deeplearning4j.eval.RegressionEvaluation
-
- RegressionEvaluation(int) - Constructor for class org.deeplearning4j.eval.RegressionEvaluation
-
Create a regression evaluation object with the specified number of columns, and default precision
for the stats() method.
- RegressionEvaluation(int, int) - Constructor for class org.deeplearning4j.eval.RegressionEvaluation
-
Create a regression evaluation object with the specified number of columns, and specified precision
for the stats() method.
- RegressionEvaluation(String...) - Constructor for class org.deeplearning4j.eval.RegressionEvaluation
-
Create a regression evaluation object with default precision for the stats() method
- RegressionEvaluation(List<String>) - Constructor for class org.deeplearning4j.eval.RegressionEvaluation
-
Create a regression evaluation object with default precision for the stats() method
- RegressionEvaluation(List<String>, int) - Constructor for class org.deeplearning4j.eval.RegressionEvaluation
-
Create a regression evaluation object with specified precision for the stats() method
- RegressionEvaluation.Metric - Enum in org.deeplearning4j.eval
-
- RegressionScoreCalculator - Class in org.deeplearning4j.earlystopping.scorecalc
-
Calculate the regression score of the network (MultiLayerNetwork or ComputationGraph) on a test set, using the
specified regression metric - RegressionEvaluation.Metric
- RegressionScoreCalculator(RegressionEvaluation.Metric, DataSetIterator) - Constructor for class org.deeplearning4j.earlystopping.scorecalc.RegressionScoreCalculator
-
- relativeSquaredError(int) - Method in class org.deeplearning4j.eval.RegressionEvaluation
-
- release(CAS) - Method in class org.deeplearning4j.text.uima.UimaResource
-
- ReliabilityDiagram - Class in org.deeplearning4j.eval.curves
-
Created by Alex on 05/07/2017.
- ReliabilityDiagram(String, double[], double[]) - Constructor for class org.deeplearning4j.eval.curves.ReliabilityDiagram
-
- reload(String) - Static method in class org.ansj.library.AmbiguityLibrary
-
刷新一个,将值设置为null
- reload(String) - Static method in class org.ansj.library.CrfLibrary
-
刷新一个,将值设置为null
- reload(String) - Static method in class org.ansj.library.DicLibrary
-
- reload(String) - Static method in class org.ansj.library.StopLibrary
-
- reload(String) - Static method in class org.ansj.library.SynonymsLibrary
-
刷新一个,将值设置为null
- reloadLibrary(String) - Static method in class org.ansj.util.MyStaticValue
-
重置一个词典
- relocatable - Variable in class org.deeplearning4j.optimize.solvers.accumulation.EncodedGradientsAccumulator
-
- remainingCapacity() - Method in class org.deeplearning4j.optimize.solvers.accumulation.FancyBlockingQueue
-
- remainingCapacity() - Method in class org.deeplearning4j.parallelism.MagicQueue
-
Deprecated.
- remoteDataUrl() - Method in class org.deeplearning4j.datasets.fetchers.CacheableExtractableDataSetFetcher
-
- remoteDataUrl(DataSetType) - Method in class org.deeplearning4j.datasets.fetchers.SvhnDataFetcher
-
- remoteDataUrl(DataSetType) - Method in class org.deeplearning4j.datasets.fetchers.TinyImageNetFetcher
-
- remoteDataUrl() - Method in class org.deeplearning4j.datasets.fetchers.UciSequenceDataFetcher
-
- remoteDataUrl(DataSetType) - Method in class org.deeplearning4j.datasets.fetchers.UciSequenceDataFetcher
-
- RemoteReceiverModule - Class in org.deeplearning4j.ui.module.remote
-
Used to receive UI updates remotely.
- RemoteReceiverModule() - Constructor for class org.deeplearning4j.ui.module.remote.RemoteReceiverModule
-
- RemoteUIStatsStorageRouter - Class in org.deeplearning4j.api.storage.impl
-
Asynchronously post all updates to a remote UI that has remote listening enabled.
Typically used with UIServer (don't forget to enable remote listener support - UIServer.getInstance().enableRemoteListener()
- RemoteUIStatsStorageRouter(String) - Constructor for class org.deeplearning4j.api.storage.impl.RemoteUIStatsStorageRouter
-
Create remote UI with defaults for all values except address
- RemoteUIStatsStorageRouter(String, int, long, double) - Constructor for class org.deeplearning4j.api.storage.impl.RemoteUIStatsStorageRouter
-
- RemoteUIStatsStorageRouter(String, String, int, long, double) - Constructor for class org.deeplearning4j.api.storage.impl.RemoteUIStatsStorageRouter
-
- remove(Object) - Method in class com.atilika.kuromoji.trie.PatriciaTrie
-
Removes entry identified by key from this trie (currently unsupported)
- remove(String) - Static method in class org.ansj.library.AmbiguityLibrary
-
删除一个key
- remove(String) - Static method in class org.ansj.library.CrfLibrary
-
删除一个key
- remove(String) - Static method in class org.ansj.library.DicLibrary
-
- remove(String) - Static method in class org.ansj.library.StopLibrary
-
- remove(String) - Static method in class org.ansj.library.SynonymsLibrary
-
删除一个key
- remove(String, String) - Static method in class org.ansj.library.SynonymsLibrary
-
从同义词组中删除掉一个词 [中国, 中华, 我国] -> remove(我国) -> [中国, 中华]
- remove() - Method in class org.deeplearning4j.aws.s3.reader.BucketIterator
-
- remove() - Method in class org.deeplearning4j.datasets.datavec.RecordReaderDataSetIterator
-
- remove() - Method in class org.deeplearning4j.datasets.datavec.RecordReaderMultiDataSetIterator
-
- remove() - Method in class org.deeplearning4j.datasets.datavec.SequenceRecordReaderDataSetIterator
-
- remove() - Method in class org.deeplearning4j.datasets.iterator.AbstractDataSetIterator
-
Removes from the underlying collection the last element returned
by this iterator (optional operation).
- remove() - Method in class org.deeplearning4j.datasets.iterator.AsyncDataSetIterator
-
Removes from the underlying collection the last element returned
by this iterator (optional operation).
- remove() - Method in class org.deeplearning4j.datasets.iterator.AsyncMultiDataSetIterator
-
Removes from the underlying collection the last element returned
by this iterator (optional operation).
- remove() - Method in class org.deeplearning4j.datasets.iterator.AsyncShieldDataSetIterator
-
Removes from the underlying collection the last element returned
by this iterator (optional operation).
- remove() - Method in class org.deeplearning4j.datasets.iterator.AsyncShieldMultiDataSetIterator
-
Removes from the underlying collection the last element returned
by this iterator (optional operation).
- remove() - Method in class org.deeplearning4j.datasets.iterator.BaseDatasetIterator
-
- remove() - Method in class org.deeplearning4j.datasets.iterator.EarlyTerminationDataSetIterator
-
- remove() - Method in class org.deeplearning4j.datasets.iterator.EarlyTerminationMultiDataSetIterator
-
- remove() - Method in class org.deeplearning4j.datasets.iterator.ExistingDataSetIterator
-
- remove() - Method in class org.deeplearning4j.datasets.iterator.file.BaseFileIterator
-
- remove() - Method in class org.deeplearning4j.datasets.iterator.FileSplitDataSetIterator
-
- remove() - Method in class org.deeplearning4j.datasets.iterator.impl.BenchmarkDataSetIterator
-
Removes from the underlying collection the last element returned
by this iterator (optional operation).
- remove() - Method in class org.deeplearning4j.datasets.iterator.impl.BenchmarkMultiDataSetIterator
-
Removes from the underlying collection the last element returned
by this iterator (optional operation).
- remove() - Method in class org.deeplearning4j.datasets.iterator.impl.ListDataSetIterator
-
- remove() - Method in class org.deeplearning4j.datasets.iterator.impl.MultiDataSetIteratorAdapter
-
- remove() - Method in class org.deeplearning4j.datasets.iterator.impl.SingletonMultiDataSetIterator
-
- remove() - Method in class org.deeplearning4j.datasets.iterator.IteratorDataSetIterator
-
- remove() - Method in class org.deeplearning4j.datasets.iterator.IteratorMultiDataSetIterator
-
- remove() - Method in class org.deeplearning4j.datasets.iterator.MultiDataSetWrapperIterator
-
- remove() - Method in class org.deeplearning4j.datasets.iterator.MultipleEpochsIterator
-
Deprecated.
Removes from the underlying collection the last element returned
by this iterator (optional operation).
- remove() - Method in class org.deeplearning4j.datasets.iterator.parallel.BaseParallelDataSetIterator
-
- remove() - Method in class org.deeplearning4j.datasets.iterator.ReconstructionDataSetIterator
-
Removes from the underlying collection the last element returned
by this iterator (optional operation).
- remove() - Method in class org.deeplearning4j.datasets.iterator.SamplingDataSetIterator
-
- remove() - Method in class org.deeplearning4j.datasets.iterator.WorkspacesShieldDataSetIterator
-
- remove() - Method in class org.deeplearning4j.datasets.test.TestDataSetIterator
-
- remove() - Method in class org.deeplearning4j.graph.graph.VertexSequence
-
- remove() - Method in class org.deeplearning4j.iterator.CnnSentenceDataSetIterator
-
- remove() - Method in class org.deeplearning4j.models.embeddings.inmemory.InMemoryLookupTable.WeightIterator
-
- remove() - Method in class org.deeplearning4j.models.sequencevectors.transformers.impl.iterables.BasicTransformerIterator
-
- remove() - Method in class org.deeplearning4j.models.word2vec.iterator.Word2VecDataSetIterator
-
Removes from the underlying collection the last element returned
by this iterator (optional operation).
- remove() - Method in class org.deeplearning4j.optimize.solvers.accumulation.FancyBlockingQueue
-
- remove(Object) - Method in class org.deeplearning4j.optimize.solvers.accumulation.FancyBlockingQueue
-
- remove() - Method in class org.deeplearning4j.parallelism.AsyncIterator
-
- remove(Object) - Method in class org.deeplearning4j.parallelism.ConcurrentHashSet
-
Deprecated.
- remove(Object) - Method in class org.deeplearning4j.parallelism.MagicQueue
-
Deprecated.
This method isn't supported
- remove() - Method in class org.deeplearning4j.parallelism.MagicQueue
-
Deprecated.
- remove() - Method in class org.deeplearning4j.spark.iterator.BaseDataSetIterator
-
- remove() - Method in class org.deeplearning4j.spark.iterator.PathSparkMultiDataSetIterator
-
- remove() - Method in class org.deeplearning4j.spark.iterator.PortableDataStreamMultiDataSetIterator
-
- remove() - Method in class org.deeplearning4j.spark.parameterserver.iterators.MultiPdsIterator
-
- remove() - Method in class org.deeplearning4j.spark.parameterserver.iterators.PdsIterator
-
- remove() - Method in class org.deeplearning4j.spark.parameterserver.iterators.VirtualDataSetIterator
-
- remove() - Method in class org.deeplearning4j.spark.parameterserver.iterators.VirtualIterator
-
- remove() - Method in class org.deeplearning4j.spark.parameterserver.iterators.VirtualMultiDataSetIterator
-
- remove() - Method in class org.deeplearning4j.text.corpora.treeparser.TreeIterator
-
Removes from the underlying collection the last element returned
by this iterator (optional operation).
- remove() - Method in class org.deeplearning4j.text.documentiterator.AsyncLabelAwareIterator
-
- remove() - Method in class org.deeplearning4j.text.documentiterator.BasicLabelAwareIterator
-
- remove() - Method in class org.deeplearning4j.text.documentiterator.FileLabelAwareIterator
-
- remove() - Method in class org.deeplearning4j.text.documentiterator.FilenamesLabelAwareIterator
-
- remove() - Method in class org.deeplearning4j.text.documentiterator.interoperability.DocumentIteratorConverter
-
- remove() - Method in class org.deeplearning4j.text.documentiterator.SimpleLabelAwareIterator
-
- remove() - Method in class org.deeplearning4j.text.sentenceiterator.interoperability.SentenceIteratorConverter
-
- remove() - Method in class org.deeplearning4j.ui.stats.sbe.StaticInfoDecoder.HwDeviceInfoGroupDecoder
-
- remove() - Method in class org.deeplearning4j.ui.stats.sbe.StaticInfoDecoder.ModelParamNamesDecoder
-
- remove() - Method in class org.deeplearning4j.ui.stats.sbe.StaticInfoDecoder.SwEnvironmentInfoDecoder
-
- remove() - Method in class org.deeplearning4j.ui.stats.sbe.StorageMetaDataDecoder.ExtraMetaDataBytesDecoder
-
- remove() - Method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder.DataSetMetaDataBytesDecoder.MetaDataBytesDecoder
-
- remove() - Method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder.DataSetMetaDataBytesDecoder
-
- remove() - Method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder.GcStatsDecoder
-
- remove() - Method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder.LayerNamesDecoder
-
- remove() - Method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder.MemoryUseDecoder
-
- remove() - Method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder.ParamNamesDecoder
-
- remove() - Method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder.PerformanceDecoder
-
- remove() - Method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder.PerParameterStatsDecoder.HistogramsDecoder.HistogramCountsDecoder
-
- remove() - Method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder.PerParameterStatsDecoder.HistogramsDecoder
-
- remove() - Method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder.PerParameterStatsDecoder
-
- remove() - Method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder.PerParameterStatsDecoder.SummaryStatDecoder
-
- remove(Object) - Method in class org.deeplearning4j.util.DiskBasedQueue
-
- remove() - Method in class org.deeplearning4j.util.DiskBasedQueue
-
- REMOVE_STOPWORDS - Static variable in class org.deeplearning4j.spark.models.embeddings.word2vec.Word2VecVariables
-
Deprecated.
- removeAll(Collection<?>) - Method in class org.deeplearning4j.optimize.solvers.accumulation.FancyBlockingQueue
-
- removeAll(Collection<?>) - Method in class org.deeplearning4j.parallelism.ConcurrentHashSet
-
Deprecated.
- removeAll(Collection<?>) - Method in class org.deeplearning4j.parallelism.MagicQueue
-
Deprecated.
This method isn't supported
- removeAll(Collection<?>) - Method in class org.deeplearning4j.util.DiskBasedQueue
-
- removeAllListeners() - Method in interface org.deeplearning4j.api.storage.StatsStorage
-
Remove all listeners from the StatsStorage instance
- removeAllListeners() - Method in class org.deeplearning4j.ui.storage.BaseCollectionStatsStorage
-
- removeAllListeners() - Method in class org.deeplearning4j.ui.storage.sqlite.J7FileStatsStorage
-
- removeClusterInfos(List<Cluster>) - Method in class org.deeplearning4j.clustering.info.ClusterSetInfo
-
- removeElement(String) - Method in class org.deeplearning4j.models.word2vec.wordstore.inmemory.AbstractCache
-
- removeElement(T) - Method in class org.deeplearning4j.models.word2vec.wordstore.inmemory.AbstractCache
-
- removeElement(String) - Method in class org.deeplearning4j.models.word2vec.wordstore.inmemory.InMemoryLookupCache
-
Deprecated.
- removeElement(VocabWord) - Method in class org.deeplearning4j.models.word2vec.wordstore.inmemory.InMemoryLookupCache
-
Deprecated.
- removeElement(String) - Method in interface org.deeplearning4j.models.word2vec.wordstore.VocabCache
-
Removes element with specified label from vocabulary
Please note: Huffman index should be updated after element removal
- removeElement(T) - Method in interface org.deeplearning4j.models.word2vec.wordstore.VocabCache
-
Removes specified element from vocabulary
Please note: Huffman index should be updated after element removal
- removeEmptyClusters(ClusterSetInfo) - Method in class org.deeplearning4j.clustering.algorithm.BaseClusteringAlgorithm
-
- removeEmptyClusters() - Method in class org.deeplearning4j.clustering.cluster.ClusterSet
-
- removeHook(TrainingHook) - Method in interface org.deeplearning4j.spark.api.TrainingMaster
-
Remove a training hook from the worker
- removeHook(TrainingHook) - Method in interface org.deeplearning4j.spark.api.TrainingWorker
-
Remove a training hook from the worker
- removeHook(TrainingHook) - Method in class org.deeplearning4j.spark.impl.paramavg.ParameterAveragingTrainingMaster
-
Remove a training hook from the worker
- removeHook(TrainingHook) - Method in class org.deeplearning4j.spark.impl.paramavg.ParameterAveragingTrainingWorker
-
Remove a training hook from the worker
- removeHook(TrainingHook) - Method in class org.deeplearning4j.spark.parameterserver.training.SharedTrainingMaster
-
- removeHook(TrainingHook) - Method in class org.deeplearning4j.spark.parameterserver.training.SharedTrainingWorker
-
- removeLayersFromOutput(int) - Method in class org.deeplearning4j.nn.transferlearning.TransferLearning.Builder
-
Remove last "n" layers of the net
At least an output layer must be added back in
- removeLibrary(String) - Static method in class org.ansj.util.MyStaticValue
-
删除一个词典
- removeOutputLayer() - Method in class org.deeplearning4j.nn.transferlearning.TransferLearning.Builder
-
Helper method to remove the outputLayer of the net.
- removePair(T, T) - Method in class org.deeplearning4j.models.glove.count.CountMap
-
- removePair(Pair<T, T>) - Method in class org.deeplearning4j.models.glove.count.CountMap
-
- removePoint(String) - Method in class org.deeplearning4j.clustering.cluster.Cluster
-
Remove the point and return it
- removePoints() - Method in class org.deeplearning4j.clustering.algorithm.BaseClusteringAlgorithm
-
- removePoints() - Method in class org.deeplearning4j.clustering.cluster.Cluster
-
Clear out the ponits
- removePoints() - Method in class org.deeplearning4j.clustering.cluster.ClusterSet
-
- removeVertex(String) - Method in class org.deeplearning4j.nn.conf.ComputationGraphConfiguration.GraphBuilder
-
Intended for use with the transfer learning API.
- removeVertex(String, boolean) - Method in class org.deeplearning4j.nn.conf.ComputationGraphConfiguration.GraphBuilder
-
Intended for use with the transfer learning API.
- removeVertexAndConnections(String) - Method in class org.deeplearning4j.nn.transferlearning.TransferLearning.GraphBuilder
-
Remove specified vertex and it's connections from the computation graph
- removeVertexKeepConnections(String) - Method in class org.deeplearning4j.nn.transferlearning.TransferLearning.GraphBuilder
-
Remove the specified vertex from the computation graph but keep it's connections.
- renderHTML(Collection<Component>) - Static method in class org.deeplearning4j.ui.standalone.StaticPageUtil
-
Given the specified components, render them to a stand-alone HTML page (which is returned as a String)
- renderHTML(Component...) - Static method in class org.deeplearning4j.ui.standalone.StaticPageUtil
-
Given the specified components, render them to a stand-alone HTML page (which is returned as a String)
- renderHTMLContent(Component...) - Static method in class org.deeplearning4j.ui.standalone.StaticPageUtil
-
- repartionData(Repartition) - Method in class org.deeplearning4j.spark.impl.paramavg.ParameterAveragingTrainingMaster.Builder
-
Set if/when repartitioning should be conducted for the training data.
Default value: always repartition (if required to guarantee correct number of partitions and correct number
of examples in each partition).
- Repartition - Enum in org.deeplearning4j.spark.api
-
- repartition - Variable in class org.deeplearning4j.spark.impl.paramavg.BaseTrainingMaster
-
- repartition - Variable in class org.deeplearning4j.spark.impl.paramavg.ParameterAveragingTrainingMaster.Builder
-
- repartition - Variable in class org.deeplearning4j.spark.parameterserver.training.SharedTrainingMaster.Builder
-
- repartition - Variable in class org.deeplearning4j.spark.parameterserver.training.SharedTrainingMaster
-
- repartition(JavaRDD<T>, Repartition, RepartitionStrategy, int, int) - Static method in class org.deeplearning4j.spark.util.SparkUtils
-
- repartitionApproximateBalance(JavaRDD<T>, Repartition, int) - Static method in class org.deeplearning4j.spark.util.SparkUtils
-
- repartitionBalanceIfRequired(JavaRDD<T>, Repartition, int, int) - Static method in class org.deeplearning4j.spark.util.SparkUtils
-
Repartition a RDD (given the
Repartition setting) such that we have approximately
numPartitions partitions, each of which has
objectsPerPartition objects.
- repartitionData(Repartition) - Method in class org.deeplearning4j.spark.parameterserver.training.SharedTrainingMaster.Builder
-
This parameter defines when repartition is applied (if applied)
- RepartitionStrategy - Enum in org.deeplearning4j.spark.api
-
RepartitionStrategy: different strategies for conducting repartitioning on training data, when repartitioning is required.
SparkDefault: repartition using Spark's standard RDD.repartition(int) method.
- repartitionStrategy - Variable in class org.deeplearning4j.spark.impl.paramavg.BaseTrainingMaster
-
- repartitionStrategy - Variable in class org.deeplearning4j.spark.impl.paramavg.ParameterAveragingTrainingMaster.Builder
-
- repartitionStrategy(RepartitionStrategy) - Method in class org.deeplearning4j.spark.impl.paramavg.ParameterAveragingTrainingMaster.Builder
-
- repartitionStrategy - Variable in class org.deeplearning4j.spark.parameterserver.training.SharedTrainingMaster.Builder
-
- repartitionStrategy(RepartitionStrategy) - Method in class org.deeplearning4j.spark.parameterserver.training.SharedTrainingMaster.Builder
-
- repartitionStrategy - Variable in class org.deeplearning4j.spark.parameterserver.training.SharedTrainingMaster
-
- replicatedModel(Model) - Method in class org.deeplearning4j.parallelism.parameterserver.ParameterServerTrainer.ParameterServerTrainerBuilder
-
- replicatedModel - Variable in class org.deeplearning4j.parallelism.trainer.DefaultTrainer
-
- reportBatch(boolean) - Method in class org.deeplearning4j.optimize.listeners.PerformanceListener.Builder
-
This method defines, if batches/sec should be reported together with other data
- reportDataSetMetaData(List<Serializable>, Class<?>) - Method in interface org.deeplearning4j.ui.stats.api.StatsReport
-
Report any metadata for the DataSet
- reportDataSetMetaData(List<Serializable>, String) - Method in interface org.deeplearning4j.ui.stats.api.StatsReport
-
Report any metadata for the DataSet
- reportDataSetMetaData(List<Serializable>, Class<?>) - Method in class org.deeplearning4j.ui.stats.impl.java.JavaStatsReport
-
- reportDataSetMetaData(List<Serializable>, String) - Method in class org.deeplearning4j.ui.stats.impl.java.JavaStatsReport
-
- reportDataSetMetaData(List<Serializable>, Class<?>) - Method in class org.deeplearning4j.ui.stats.impl.SbeStatsReport
-
- reportDataSetMetaData(List<Serializable>, String) - Method in class org.deeplearning4j.ui.stats.impl.SbeStatsReport
-
- reportETL(boolean) - Method in class org.deeplearning4j.optimize.listeners.PerformanceListener.Builder
-
This method defines, if ETL time per iteration should be reported together with other data
- reportGarbageCollection(String, int, int) - Method in interface org.deeplearning4j.ui.stats.api.StatsReport
-
Report Garbage collection stats
- reportGarbageCollection(String, int, int) - Method in class org.deeplearning4j.ui.stats.impl.java.JavaStatsReport
-
- reportGarbageCollection(String, int, int) - Method in class org.deeplearning4j.ui.stats.impl.SbeStatsReport
-
- reportHardwareInfo(int, int, long, long, long[], String[], String) - Method in interface org.deeplearning4j.ui.stats.api.StatsInitializationReport
-
- reportHardwareInfo(int, int, long, long, long[], String[], String) - Method in class org.deeplearning4j.ui.stats.impl.java.JavaStatsInitializationReport
-
- reportHardwareInfo(int, int, long, long, long[], String[], String) - Method in class org.deeplearning4j.ui.stats.impl.SbeStatsInitializationReport
-
- reportHistograms(StatsType, Map<String, Histogram>) - Method in interface org.deeplearning4j.ui.stats.api.StatsReport
-
Report histograms for all parameters, for a given
StatsType
- reportHistograms(StatsType, Map<String, Histogram>) - Method in class org.deeplearning4j.ui.stats.impl.java.JavaStatsReport
-
- reportHistograms(StatsType, Map<String, Histogram>) - Method in class org.deeplearning4j.ui.stats.impl.SbeStatsReport
-
- reportIDs(String, String, String, long) - Method in interface org.deeplearning4j.ui.stats.api.StatsInitializationReport
-
- reportIDs(String, String, String, long) - Method in interface org.deeplearning4j.ui.stats.api.StatsReport
-
- reportIDs(String, String, String, long) - Method in class org.deeplearning4j.ui.stats.impl.java.JavaStatsInitializationReport
-
- reportIDs(String, String, String, long) - Method in class org.deeplearning4j.ui.stats.impl.java.JavaStatsReport
-
- reportIDs(String, String, String, long) - Method in class org.deeplearning4j.ui.stats.impl.SbeStatsInitializationReport
-
- reportIDs(String, String, String, long) - Method in class org.deeplearning4j.ui.stats.impl.SbeStatsReport
-
- reportingFrequency() - Method in interface org.deeplearning4j.ui.stats.api.StatsUpdateConfiguration
-
Get the reporting frequency, in terms of listener calls
- reportingFrequency(int) - Method in class org.deeplearning4j.ui.stats.impl.DefaultStatsUpdateConfiguration.Builder
-
- reportingFrequency() - Method in class org.deeplearning4j.ui.stats.impl.DefaultStatsUpdateConfiguration
-
- reportIteration(boolean) - Method in class org.deeplearning4j.optimize.listeners.PerformanceListener.Builder
-
This method defines, if iteration number should be reported together with other data
- reportIterationCount(int) - Method in interface org.deeplearning4j.ui.stats.api.StatsReport
-
Report the current iteration number
- reportIterationCount(int) - Method in class org.deeplearning4j.ui.stats.impl.java.JavaStatsReport
-
- reportIterationCount(int) - Method in class org.deeplearning4j.ui.stats.impl.SbeStatsReport
-
- reportLearningRates(Map<String, Double>) - Method in interface org.deeplearning4j.ui.stats.api.StatsReport
-
Report the learning rates by parameter
- reportLearningRates(Map<String, Double>) - Method in class org.deeplearning4j.ui.stats.impl.java.JavaStatsReport
-
- reportLearningRates(Map<String, Double>) - Method in class org.deeplearning4j.ui.stats.impl.SbeStatsReport
-
- reportMean(StatsType, Map<String, Double>) - Method in interface org.deeplearning4j.ui.stats.api.StatsReport
-
Report the mean values for each parameter, the given StatsType (Parameters/Updates/Activations)
- reportMean(StatsType, Map<String, Double>) - Method in class org.deeplearning4j.ui.stats.impl.java.JavaStatsReport
-
- reportMean(StatsType, Map<String, Double>) - Method in class org.deeplearning4j.ui.stats.impl.SbeStatsReport
-
- reportMeanMagnitudes(StatsType, Map<String, Double>) - Method in interface org.deeplearning4j.ui.stats.api.StatsReport
-
Report the mean magnitude values for each parameter for the given StatsType (Parameters/Updates/Activations)
- reportMeanMagnitudes(StatsType, Map<String, Double>) - Method in class org.deeplearning4j.ui.stats.impl.java.JavaStatsReport
-
- reportMeanMagnitudes(StatsType, Map<String, Double>) - Method in class org.deeplearning4j.ui.stats.impl.SbeStatsReport
-
- reportMemoryUse(long, long, long, long, long[], long[]) - Method in interface org.deeplearning4j.ui.stats.api.StatsReport
-
Report the memory stats at this iteration
- reportMemoryUse(long, long, long, long, long[], long[]) - Method in class org.deeplearning4j.ui.stats.impl.java.JavaStatsReport
-
- reportMemoryUse(long, long, long, long, long[], long[]) - Method in class org.deeplearning4j.ui.stats.impl.SbeStatsReport
-
- reportModelInfo(String, String, String[], int, long) - Method in interface org.deeplearning4j.ui.stats.api.StatsInitializationReport
-
Report the model information
- reportModelInfo(String, String, String[], int, long) - Method in class org.deeplearning4j.ui.stats.impl.java.JavaStatsInitializationReport
-
- reportModelInfo(String, String, String[], int, long) - Method in class org.deeplearning4j.ui.stats.impl.SbeStatsInitializationReport
-
- reportPerformance(long, long, long, double, double) - Method in interface org.deeplearning4j.ui.stats.api.StatsReport
-
Report the performance stats (since the last report)
- reportPerformance(long, long, long, double, double) - Method in class org.deeplearning4j.ui.stats.impl.java.JavaStatsReport
-
- reportPerformance(long, long, long, double, double) - Method in class org.deeplearning4j.ui.stats.impl.SbeStatsReport
-
- reportSample(boolean) - Method in class org.deeplearning4j.optimize.listeners.PerformanceListener.Builder
-
This method defines, if samples/sec should be reported together with other data
- reportScore(boolean) - Method in class org.deeplearning4j.optimize.listeners.PerformanceListener.Builder
-
This method defines, if score should be reported together with other data
- reportScore - Variable in class org.deeplearning4j.parallelism.ParallelWrapper.Builder
-
- reportScore - Variable in class org.deeplearning4j.parallelism.ParallelWrapper
-
- reportScore(double) - Method in interface org.deeplearning4j.ui.stats.api.StatsReport
-
Report model score at the current iteration
- reportScore(double) - Method in class org.deeplearning4j.ui.stats.impl.java.JavaStatsReport
-
- reportScore(double) - Method in class org.deeplearning4j.ui.stats.impl.SbeStatsReport
-
- reportScoreAfterAveraging(boolean) - Method in class org.deeplearning4j.parallelism.ParallelWrapper.Builder
-
This method enables/disables averaged model score reporting
- reportSoftwareInfo(String, String, String, String, String, String, String, String, String, Map<String, String>) - Method in interface org.deeplearning4j.ui.stats.api.StatsInitializationReport
-
- reportSoftwareInfo(String, String, String, String, String, String, String, String, String, Map<String, String>) - Method in class org.deeplearning4j.ui.stats.impl.java.JavaStatsInitializationReport
-
- reportSoftwareInfo(String, String, String, String, String, String, String, String, String, Map<String, String>) - Method in class org.deeplearning4j.ui.stats.impl.SbeStatsInitializationReport
-
- reportStatsCollectionDurationMS(int) - Method in interface org.deeplearning4j.ui.stats.api.StatsReport
-
Report the number of milliseconds required to calculate all of the stats.
- reportStatsCollectionDurationMS(int) - Method in class org.deeplearning4j.ui.stats.impl.java.JavaStatsReport
-
- reportStatsCollectionDurationMS(int) - Method in class org.deeplearning4j.ui.stats.impl.SbeStatsReport
-
- reportStdev(StatsType, Map<String, Double>) - Method in interface org.deeplearning4j.ui.stats.api.StatsReport
-
Report the standard deviation values for each parameter for the given StatsType (Parameters/Updates/Activations)
- reportStdev(StatsType, Map<String, Double>) - Method in class org.deeplearning4j.ui.stats.impl.java.JavaStatsReport
-
- reportStdev(StatsType, Map<String, Double>) - Method in class org.deeplearning4j.ui.stats.impl.SbeStatsReport
-
- reportStorageEvents(Collection<StatsStorageEvent>) - Method in interface org.deeplearning4j.ui.api.UIModule
-
Whenever the
UIServer receives some
StatsStorageEvents from one of the registered
StatsStorage
instances, it will filter these and pass on to the UI module those ones that match one of the Type IDs from
UIModule.getCallbackTypeIDs().
Typically, these will be batched together at least somewhat, rather than being reported individually.
- reportStorageEvents(Collection<StatsStorageEvent>) - Method in class org.deeplearning4j.ui.module.convolutional.ConvolutionalListenerModule
-
- reportStorageEvents(Collection<StatsStorageEvent>) - Method in class org.deeplearning4j.ui.module.defaultModule.DefaultModule
-
- reportStorageEvents(Collection<StatsStorageEvent>) - Method in class org.deeplearning4j.ui.module.remote.RemoteReceiverModule
-
- reportStorageEvents(Collection<StatsStorageEvent>) - Method in class org.deeplearning4j.ui.module.train.TrainModule
-
- reportStorageEvents(Collection<StatsStorageEvent>) - Method in class org.deeplearning4j.ui.module.tsne.TsneModule
-
- reportTime(boolean) - Method in class org.deeplearning4j.optimize.listeners.PerformanceListener.Builder
-
This method defines, if time per iteration should be reported together with other data
- requiresDropoutFromLegacy(Layer[]) - Method in class org.deeplearning4j.nn.conf.serde.BaseNetConfigDeserializer
-
- requiresIUpdaterFromLegacy(Layer[]) - Method in class org.deeplearning4j.nn.conf.serde.BaseNetConfigDeserializer
-
- reset() - Method in class org.deeplearning4j.datasets.datavec.RecordReaderDataSetIterator
-
- reset() - Method in class org.deeplearning4j.datasets.datavec.RecordReaderMultiDataSetIterator
-
- reset() - Method in class org.deeplearning4j.datasets.datavec.SequenceRecordReaderDataSetIterator
-
- reset() - Method in class org.deeplearning4j.datasets.fetchers.MnistDataFetcher
-
- reset() - Method in class org.deeplearning4j.datasets.iterator.AbstractDataSetIterator
-
Resets the iterator back to the beginning
- reset() - Method in class org.deeplearning4j.datasets.iterator.AsyncDataSetIterator
-
Resets the iterator back to the beginning
- reset() - Method in class org.deeplearning4j.datasets.iterator.AsyncMultiDataSetIterator
-
Resets the iterator back to the beginning
- reset() - Method in class org.deeplearning4j.datasets.iterator.AsyncShieldDataSetIterator
-
Resets the iterator back to the beginning
- reset() - Method in class org.deeplearning4j.datasets.iterator.AsyncShieldMultiDataSetIterator
-
Resets the iterator back to the beginning
- reset() - Method in class org.deeplearning4j.datasets.iterator.BaseDatasetIterator
-
- reset() - Method in interface org.deeplearning4j.datasets.iterator.callbacks.DataSetCallback
-
- reset() - Method in class org.deeplearning4j.datasets.iterator.callbacks.DefaultCallback
-
- reset() - Method in class org.deeplearning4j.datasets.iterator.callbacks.InterleavedDataSetCallback
-
- reset() - Method in interface org.deeplearning4j.datasets.iterator.DataSetFetcher
-
Deprecated.
Returns the fetcher back to the beginning of the dataset
- reset() - Method in class org.deeplearning4j.datasets.iterator.EarlyTerminationDataSetIterator
-
- reset() - Method in class org.deeplearning4j.datasets.iterator.EarlyTerminationMultiDataSetIterator
-
- reset() - Method in class org.deeplearning4j.datasets.iterator.ExistingDataSetIterator
-
- reset() - Method in class org.deeplearning4j.datasets.iterator.file.BaseFileIterator
-
- reset() - Method in class org.deeplearning4j.datasets.iterator.FileSplitDataSetIterator
-
- reset() - Method in class org.deeplearning4j.datasets.iterator.impl.BenchmarkDataSetIterator
-
- reset() - Method in class org.deeplearning4j.datasets.iterator.impl.BenchmarkMultiDataSetIterator
-
- reset() - Method in class org.deeplearning4j.datasets.iterator.impl.CifarDataSetIterator
-
- reset() - Method in class org.deeplearning4j.datasets.iterator.impl.ListDataSetIterator
-
- reset() - Method in class org.deeplearning4j.datasets.iterator.impl.MultiDataSetIteratorAdapter
-
- reset() - Method in class org.deeplearning4j.datasets.iterator.impl.SingletonMultiDataSetIterator
-
- reset() - Method in class org.deeplearning4j.datasets.iterator.IteratorDataSetIterator
-
- reset() - Method in class org.deeplearning4j.datasets.iterator.IteratorMultiDataSetIterator
-
- reset() - Method in class org.deeplearning4j.datasets.iterator.MultiDataSetWrapperIterator
-
- reset() - Method in class org.deeplearning4j.datasets.iterator.MultipleEpochsIterator
-
Deprecated.
Resets the iterator back to the beginning
- reset() - Method in class org.deeplearning4j.datasets.iterator.parallel.BaseParallelDataSetIterator
-
- reset(int) - Method in class org.deeplearning4j.datasets.iterator.parallel.BaseParallelDataSetIterator
-
- reset(int) - Method in class org.deeplearning4j.datasets.iterator.parallel.FileSplitParallelDataSetIterator
-
- reset(int) - Method in class org.deeplearning4j.datasets.iterator.parallel.JointParallelDataSetIterator
-
- reset() - Method in class org.deeplearning4j.datasets.iterator.ReconstructionDataSetIterator
-
Resets the iterator back to the beginning
- reset() - Method in class org.deeplearning4j.datasets.iterator.SamplingDataSetIterator
-
- reset() - Method in class org.deeplearning4j.datasets.iterator.WorkspacesShieldDataSetIterator
-
- reset() - Method in class org.deeplearning4j.datasets.test.TestDataSetIterator
-
- reset() - Method in class org.deeplearning4j.earlystopping.scorecalc.AutoencoderScoreCalculator
-
- reset() - Method in class org.deeplearning4j.earlystopping.scorecalc.base.BaseScoreCalculator
-
- reset() - Method in class org.deeplearning4j.earlystopping.scorecalc.DataSetLossCalculator
-
- reset() - Method in class org.deeplearning4j.earlystopping.scorecalc.VAEReconErrorScoreCalculator
-
- reset() - Method in class org.deeplearning4j.earlystopping.scorecalc.VAEReconProbScoreCalculator
-
- reset() - Method in class org.deeplearning4j.earlystopping.trainer.BaseEarlyStoppingTrainer
-
- reset() - Method in class org.deeplearning4j.eval.Evaluation
-
- reset() - Method in class org.deeplearning4j.eval.EvaluationBinary
-
- reset() - Method in class org.deeplearning4j.eval.EvaluationCalibration
-
- reset() - Method in interface org.deeplearning4j.eval.IEvaluation
-
- reset() - Method in class org.deeplearning4j.eval.RegressionEvaluation
-
- reset() - Method in class org.deeplearning4j.eval.ROC
-
- reset() - Method in class org.deeplearning4j.eval.ROCBinary
-
- reset() - Method in class org.deeplearning4j.eval.ROCMultiClass
-
- reset() - Method in interface org.deeplearning4j.graph.iterator.GraphWalkIterator
-
Reset the graph walk iterator.
- reset() - Method in class org.deeplearning4j.graph.iterator.RandomWalkIterator
-
- reset() - Method in class org.deeplearning4j.graph.iterator.WeightedRandomWalkIterator
-
- reset() - Method in class org.deeplearning4j.iterator.CnnSentenceDataSetIterator
-
- reset() - Method in interface org.deeplearning4j.iterator.LabeledSentenceProvider
-
Reset the iterator - including shuffling the order, if necessary/appropriate
- reset() - Method in class org.deeplearning4j.iterator.provider.CollectionLabeledSentenceProvider
-
- reset() - Method in class org.deeplearning4j.iterator.provider.FileLabeledSentenceProvider
-
- reset() - Method in class org.deeplearning4j.iterator.provider.LabelAwareConverter
-
- reset(boolean) - Method in interface org.deeplearning4j.models.sequencevectors.graph.walkers.GraphWalker
-
This method resets walker
- reset(boolean) - Method in class org.deeplearning4j.models.sequencevectors.graph.walkers.impl.NearestVertexWalker
-
- reset(boolean) - Method in class org.deeplearning4j.models.sequencevectors.graph.walkers.impl.PopularityWalker
-
- reset(boolean) - Method in class org.deeplearning4j.models.sequencevectors.graph.walkers.impl.RandomWalker
-
This method resets walker
- reset(boolean) - Method in class org.deeplearning4j.models.sequencevectors.graph.walkers.impl.WeightedWalker
-
This method resets walker
- reset() - Method in interface org.deeplearning4j.models.sequencevectors.interfaces.SequenceIterator
-
- reset() - Method in class org.deeplearning4j.models.sequencevectors.iterators.AbstractSequenceIterator
-
Resets iterator to first position
- reset() - Method in class org.deeplearning4j.models.sequencevectors.iterators.FilteredSequenceIterator
-
Resets iterator down to first sequence
- reset() - Method in class org.deeplearning4j.models.sequencevectors.iterators.SynchronizedSequenceIterator
-
This method resets underlying iterator
- reset() - Method in class org.deeplearning4j.models.sequencevectors.transformers.impl.iterables.BasicTransformerIterator
-
- reset() - Method in class org.deeplearning4j.models.sequencevectors.transformers.impl.iterables.ParallelTransformerIterator
-
- reset() - Method in class org.deeplearning4j.models.sequencevectors.transformers.impl.SentenceTransformer
-
- reset() - Method in interface org.deeplearning4j.models.sequencevectors.transformers.SequenceTransformer
-
- reset() - Method in class org.deeplearning4j.models.word2vec.iterator.Word2VecDataFetcher
-
- reset() - Method in class org.deeplearning4j.models.word2vec.iterator.Word2VecDataSetIterator
-
- reset() - Method in class org.deeplearning4j.optimize.solvers.accumulation.BasicGradientsAccumulator
-
This method resets all accumulated updates (if any)
- reset() - Method in class org.deeplearning4j.optimize.solvers.accumulation.EncodedGradientsAccumulator
-
This method resets all accumulated updates (if any)
- reset() - Method in interface org.deeplearning4j.optimize.solvers.accumulation.GradientsAccumulator
-
This method resets all accumulated updates (if any)
- reset() - Method in class org.deeplearning4j.parallelism.EarlyStoppingParallelTrainer
-
- reset() - Method in class org.deeplearning4j.spark.datavec.iterator.SparkSourceDummyReader
-
- reset() - Method in class org.deeplearning4j.spark.iterator.BaseDataSetIterator
-
- reset() - Method in class org.deeplearning4j.spark.iterator.PathSparkMultiDataSetIterator
-
- reset() - Method in class org.deeplearning4j.spark.iterator.PortableDataStreamMultiDataSetIterator
-
- reset() - Method in class org.deeplearning4j.spark.parameterserver.iterators.VirtualDataSetIterator
-
- reset() - Method in class org.deeplearning4j.spark.parameterserver.iterators.VirtualMultiDataSetIterator
-
- reset() - Method in class org.deeplearning4j.text.documentiterator.AsyncLabelAwareIterator
-
- reset() - Method in class org.deeplearning4j.text.documentiterator.BasicLabelAwareIterator
-
This methods resets LabelAwareIterator
- reset() - Method in interface org.deeplearning4j.text.documentiterator.DocumentIterator
-
Reset the iterator to the beginning
- reset() - Method in class org.deeplearning4j.text.documentiterator.FileDocumentIterator
-
- reset() - Method in class org.deeplearning4j.text.documentiterator.FileLabelAwareIterator
-
- reset() - Method in class org.deeplearning4j.text.documentiterator.FilenamesLabelAwareIterator
-
- reset() - Method in class org.deeplearning4j.text.documentiterator.interoperability.DocumentIteratorConverter
-
- reset() - Method in interface org.deeplearning4j.text.documentiterator.LabelAwareIterator
-
- reset() - Method in class org.deeplearning4j.text.documentiterator.LabelsSource
-
This method should be called from Iterator's reset() method, to keep labels in sync with iterator
- reset() - Method in class org.deeplearning4j.text.documentiterator.SimpleLabelAwareIterator
-
This methods resets LabelAwareIterator by creating new Iterator from Iterable internally
- reset() - Method in class org.deeplearning4j.text.sentenceiterator.AggregatingSentenceIterator
-
- reset() - Method in class org.deeplearning4j.text.sentenceiterator.BasicLineIterator
-
- reset() - Method in class org.deeplearning4j.text.sentenceiterator.BasicResultSetIterator
-
- reset() - Method in class org.deeplearning4j.text.sentenceiterator.CollectionSentenceIterator
-
- reset() - Method in class org.deeplearning4j.text.sentenceiterator.FileSentenceIterator
-
- reset() - Method in class org.deeplearning4j.text.sentenceiterator.interoperability.SentenceIteratorConverter
-
- reset() - Method in class org.deeplearning4j.text.sentenceiterator.LineSentenceIterator
-
- reset() - Method in class org.deeplearning4j.text.sentenceiterator.MutipleEpochsSentenceIterator
-
- reset() - Method in class org.deeplearning4j.text.sentenceiterator.PrefetchingSentenceIterator
-
Deprecated.
- reset() - Method in interface org.deeplearning4j.text.sentenceiterator.SentenceIterator
-
Resets the iterator to the beginning
- reset() - Method in class org.deeplearning4j.text.sentenceiterator.StreamLineIterator
-
- reset() - Method in class org.deeplearning4j.text.sentenceiterator.SynchronizedSentenceIterator
-
- reset() - Method in class org.deeplearning4j.text.sentenceiterator.UimaResultSetIterator
-
- reset() - Method in class org.deeplearning4j.text.sentenceiterator.UimaSentenceIterator
-
- resetContent(AnsjReader) - Method in class org.ansj.splitWord.Analysis
-
重置分词器
- resetContent(Reader) - Method in class org.ansj.splitWord.Analysis
-
- resetContent(Reader, int) - Method in class org.ansj.splitWord.Analysis
-
- resetLayerDefaultConfig() - Method in class org.deeplearning4j.nn.conf.layers.BaseLayer
-
Reset the learning related configs of the layer to default.
- resetLayerDefaultConfig() - Method in class org.deeplearning4j.nn.conf.layers.Layer
-
Reset the learning related configs of the layer to default.
- resetModel - Variable in class org.deeplearning4j.models.embeddings.wordvectors.WordVectorsImpl
-
- resetModel(boolean) - Method in class org.deeplearning4j.models.glove.Glove.Builder
-
- resetModel(boolean) - Method in class org.deeplearning4j.models.node2vec.Node2Vec.Builder
-
Deprecated.
- resetModel(boolean) - Method in class org.deeplearning4j.models.paragraphvectors.ParagraphVectors.Builder
-
This method defines whether model should be totally wiped out prior building, or not
- resetModel - Variable in class org.deeplearning4j.models.sequencevectors.SequenceVectors.Builder
-
- resetModel(boolean) - Method in class org.deeplearning4j.models.sequencevectors.SequenceVectors.Builder
-
This method defines, should all model be reset before training.
- resetModel(boolean) - Method in class org.deeplearning4j.models.word2vec.Word2Vec.Builder
-
This method defines whether model should be totally wiped out prior building, or not
- resetPending - Variable in class org.deeplearning4j.datasets.iterator.DataSetIteratorSplitter
-
- resetPending - Variable in class org.deeplearning4j.datasets.iterator.MultiDataSetIteratorSplitter
-
- resetSupported() - Method in class org.deeplearning4j.datasets.datavec.RecordReaderDataSetIterator
-
- resetSupported() - Method in class org.deeplearning4j.datasets.datavec.RecordReaderMultiDataSetIterator
-
- resetSupported() - Method in class org.deeplearning4j.datasets.datavec.SequenceRecordReaderDataSetIterator
-
- resetSupported() - Method in class org.deeplearning4j.datasets.iterator.AbstractDataSetIterator
-
- resetSupported() - Method in class org.deeplearning4j.datasets.iterator.AsyncDataSetIterator
-
Is resetting supported by this DataSetIterator? Many DataSetIterators do support resetting,
but some don't
- resetSupported() - Method in class org.deeplearning4j.datasets.iterator.AsyncMultiDataSetIterator
-
Is resetting supported by this DataSetIterator? Many DataSetIterators do support resetting,
but some don't
- resetSupported() - Method in class org.deeplearning4j.datasets.iterator.AsyncShieldDataSetIterator
-
Is resetting supported by this DataSetIterator? Many DataSetIterators do support resetting,
but some don't
- resetSupported() - Method in class org.deeplearning4j.datasets.iterator.AsyncShieldMultiDataSetIterator
-
Is resetting supported by this DataSetIterator? Many DataSetIterators do support resetting,
but some don't
- resetSupported() - Method in class org.deeplearning4j.datasets.iterator.BaseDatasetIterator
-
- resetSupported() - Method in class org.deeplearning4j.datasets.iterator.EarlyTerminationDataSetIterator
-
- resetSupported() - Method in class org.deeplearning4j.datasets.iterator.EarlyTerminationMultiDataSetIterator
-
- resetSupported() - Method in class org.deeplearning4j.datasets.iterator.ExistingDataSetIterator
-
- resetSupported() - Method in class org.deeplearning4j.datasets.iterator.file.BaseFileIterator
-
- resetSupported() - Method in class org.deeplearning4j.datasets.iterator.FileSplitDataSetIterator
-
- resetSupported() - Method in class org.deeplearning4j.datasets.iterator.impl.BenchmarkDataSetIterator
-
- resetSupported() - Method in class org.deeplearning4j.datasets.iterator.impl.BenchmarkMultiDataSetIterator
-
- resetSupported() - Method in class org.deeplearning4j.datasets.iterator.impl.CifarDataSetIterator
-
- resetSupported() - Method in class org.deeplearning4j.datasets.iterator.impl.ListDataSetIterator
-
- resetSupported() - Method in class org.deeplearning4j.datasets.iterator.impl.MultiDataSetIteratorAdapter
-
- resetSupported() - Method in class org.deeplearning4j.datasets.iterator.impl.SingletonMultiDataSetIterator
-
- resetSupported() - Method in class org.deeplearning4j.datasets.iterator.IteratorDataSetIterator
-
- resetSupported() - Method in class org.deeplearning4j.datasets.iterator.IteratorMultiDataSetIterator
-
- resetSupported() - Method in class org.deeplearning4j.datasets.iterator.MultiDataSetWrapperIterator
-
- resetSupported() - Method in class org.deeplearning4j.datasets.iterator.MultipleEpochsIterator
-
Deprecated.
- resetSupported() - Method in class org.deeplearning4j.datasets.iterator.parallel.BaseParallelDataSetIterator
-
- resetSupported() - Method in class org.deeplearning4j.datasets.iterator.ReconstructionDataSetIterator
-
- resetSupported() - Method in class org.deeplearning4j.datasets.iterator.SamplingDataSetIterator
-
- resetSupported() - Method in class org.deeplearning4j.datasets.iterator.WorkspacesShieldDataSetIterator
-
- resetSupported() - Method in class org.deeplearning4j.datasets.test.TestDataSetIterator
-
- resetSupported() - Method in class org.deeplearning4j.iterator.CnnSentenceDataSetIterator
-
- resetSupported() - Method in class org.deeplearning4j.models.word2vec.iterator.Word2VecDataSetIterator
-
- resetSupported() - Method in class org.deeplearning4j.spark.datavec.iterator.SparkSourceDummyReader
-
- resetSupported() - Method in class org.deeplearning4j.spark.iterator.BaseDataSetIterator
-
- resetSupported() - Method in class org.deeplearning4j.spark.iterator.PathSparkMultiDataSetIterator
-
- resetSupported() - Method in class org.deeplearning4j.spark.iterator.PortableDataStreamMultiDataSetIterator
-
- resetSupported() - Method in class org.deeplearning4j.spark.parameterserver.iterators.VirtualDataSetIterator
-
- resetSupported() - Method in class org.deeplearning4j.spark.parameterserver.iterators.VirtualMultiDataSetIterator
-
- resetTracker - Variable in class org.deeplearning4j.datasets.iterator.parallel.BaseParallelDataSetIterator
-
- resetVariables() - Method in class org.deeplearning4j.nn.conf.NeuralNetConfiguration
-
- resetWeights() - Method in interface org.deeplearning4j.graph.models.embeddings.GraphVectorLookupTable
-
Reset (randomize) the weights.
- resetWeights() - Method in class org.deeplearning4j.graph.models.embeddings.InMemoryGraphLookupTable
-
- resetWeights(boolean) - Method in class org.deeplearning4j.models.embeddings.inmemory.InMemoryLookupTable
-
- resetWeights() - Method in class org.deeplearning4j.models.embeddings.inmemory.InMemoryLookupTable
-
Reset the weights of the cache
- resetWeights(boolean) - Method in interface org.deeplearning4j.models.embeddings.WeightLookupTable
-
Clear out all weights regardless
- resetWeights() - Method in interface org.deeplearning4j.models.embeddings.WeightLookupTable
-
Reset the weights of the cache
- resetWeights(boolean) - Method in class org.deeplearning4j.models.glove.GloveWeightLookupTable
-
Deprecated.
- resetWeights() - Method in class org.deeplearning4j.models.glove.GloveWeightLookupTable
-
Deprecated.
Reset the weights of the cache
- resetWordCounters() - Method in class org.deeplearning4j.models.word2vec.wordstore.VocabularyHolder
-
This methods reset counters for all words in vocabulary
- reshape2dTo3d(INDArray, int) - Static method in class org.deeplearning4j.util.TimeSeriesUtils
-
- reshape2dTo3d(INDArray, int, LayerWorkspaceMgr, ArrayType) - Static method in class org.deeplearning4j.util.TimeSeriesUtils
-
- reshape2dTo4d(INDArray, int[], LayerWorkspaceMgr, ArrayType) - Static method in class org.deeplearning4j.util.ConvolutionUtils
-
- reshape3dMask(INDArray, LayerWorkspaceMgr, ArrayType) - Static method in class org.deeplearning4j.util.ConvolutionUtils
-
- reshape3dTo2d(INDArray) - Static method in class org.deeplearning4j.util.TimeSeriesUtils
-
- reshape3dTo2d(INDArray, LayerWorkspaceMgr, ArrayType) - Static method in class org.deeplearning4j.util.TimeSeriesUtils
-
- reshape4dMask(INDArray, LayerWorkspaceMgr, ArrayType) - Static method in class org.deeplearning4j.util.ConvolutionUtils
-
- reshape4dTo2d(INDArray, LayerWorkspaceMgr, ArrayType) - Static method in class org.deeplearning4j.util.ConvolutionUtils
-
- reshapeMaskIfRequired(INDArray, INDArray, LayerWorkspaceMgr, ArrayType) - Static method in class org.deeplearning4j.util.ConvolutionUtils
-
- reshapeOrder - Variable in class org.deeplearning4j.nn.conf.graph.ReshapeVertex
-
- reshapePerOutputTimeSeriesMaskTo2d(INDArray) - Static method in class org.deeplearning4j.util.TimeSeriesUtils
-
- reshapePerOutputTimeSeriesMaskTo2d(INDArray, LayerWorkspaceMgr, ArrayType) - Static method in class org.deeplearning4j.util.TimeSeriesUtils
-
- ReshapePreprocessor - Class in org.deeplearning4j.nn.modelimport.keras.preprocessors
-
Generic reshape preprocessor
- ReshapePreprocessor(int[], int[]) - Constructor for class org.deeplearning4j.nn.modelimport.keras.preprocessors.ReshapePreprocessor
-
- reshapeTimeSeriesMaskToVector(INDArray) - Static method in class org.deeplearning4j.util.TimeSeriesUtils
-
Reshape time series mask arrays.
- reshapeTimeSeriesMaskToVector(INDArray, LayerWorkspaceMgr, ArrayType) - Static method in class org.deeplearning4j.util.TimeSeriesUtils
-
Reshape time series mask arrays.
- reshapeTimeSeriesTo2d(INDArray) - Static method in class org.deeplearning4j.eval.EvaluationUtils
-
- reshapeVectorToTimeSeriesMask(INDArray, int) - Static method in class org.deeplearning4j.util.TimeSeriesUtils
-
Reshape time series mask arrays.
- ReshapeVertex - Class in org.deeplearning4j.nn.conf.graph
-
Adds the ability to reshape and flatten the tensor in the computation graph.
NOTE: This class should only be used if you know exactly what you are doing with reshaping activations.
- ReshapeVertex(int...) - Constructor for class org.deeplearning4j.nn.conf.graph.ReshapeVertex
-
- ReshapeVertex(char, int[], int[]) - Constructor for class org.deeplearning4j.nn.conf.graph.ReshapeVertex
-
- ReshapeVertex - Class in org.deeplearning4j.nn.graph.vertex.impl
-
Adds the ability to reshape and flatten the tensor in the computation graph.
- ReshapeVertex(ComputationGraph, String, int, char, int[], int[]) - Constructor for class org.deeplearning4j.nn.graph.vertex.impl.ReshapeVertex
-
- ReshapeVertex(ComputationGraph, String, int, VertexIndices[], VertexIndices[], char, int[], int[]) - Constructor for class org.deeplearning4j.nn.graph.vertex.impl.ReshapeVertex
-
- reshapeWeights(int[], INDArray) - Static method in class org.deeplearning4j.nn.weights.WeightInitUtil
-
Reshape the parameters view, without modifying the paramsView array values.
- reshapeWeights(int[], INDArray, char) - Static method in class org.deeplearning4j.nn.weights.WeightInitUtil
-
Reshape the parameters view, without modifying the paramsView array values.
- ResNet50 - Class in org.deeplearning4j.zoo.model
-
Residual networks for deep learning.
- resolve(String) - Method in class com.atilika.kuromoji.util.FileResourceResolver
-
- resolve(String) - Method in interface com.atilika.kuromoji.util.ResourceResolver
-
Resolve the resource name and return an open input stream to it.
- resolve(String) - Method in class com.atilika.kuromoji.util.SimpleResourceResolver
-
- resolve(DeserializationContext) - Method in class org.deeplearning4j.nn.conf.serde.BaseNetConfigDeserializer
-
- resolver - Variable in class com.atilika.kuromoji.TokenizerBase.Builder
-
- ResourceResolver - Interface in com.atilika.kuromoji.util
-
An adapter to resolve the required resources into data streams.
- restoreComputationGraph(String) - Static method in class org.deeplearning4j.util.ModelSerializer
-
Load a computation graph from a file
- restoreComputationGraph(String, boolean) - Static method in class org.deeplearning4j.util.ModelSerializer
-
Load a computation graph from a file
- restoreComputationGraph(InputStream, boolean) - Static method in class org.deeplearning4j.util.ModelSerializer
-
Load a computation graph from a InputStream
- restoreComputationGraph(InputStream) - Static method in class org.deeplearning4j.util.ModelSerializer
-
Load a computation graph from a InputStream
- restoreComputationGraph(File) - Static method in class org.deeplearning4j.util.ModelSerializer
-
Load a computation graph from a file
- restoreComputationGraph(File, boolean) - Static method in class org.deeplearning4j.util.ModelSerializer
-
Load a computation graph from a file
- restoreComputationGraphAndNormalizer(InputStream, boolean) - Static method in class org.deeplearning4j.util.ModelSerializer
-
Restore a ComputationGraph and Normalizer (if present - null if not) from the InputStream.
- restoreComputationGraphAndNormalizer(File, boolean) - Static method in class org.deeplearning4j.util.ModelSerializer
-
Restore a ComputationGraph and Normalizer (if present - null if not) from a File
- restoreModel(InputStream) - Method in class org.deeplearning4j.nn.modelexport.solr.ltr.model.ScoringModel
-
- restoreMultiLayerNetwork(File) - Static method in class org.deeplearning4j.util.ModelSerializer
-
Load a multi layer network from a file
- restoreMultiLayerNetwork(File, boolean) - Static method in class org.deeplearning4j.util.ModelSerializer
-
Load a multi layer network from a file
- restoreMultiLayerNetwork(InputStream, boolean) - Static method in class org.deeplearning4j.util.ModelSerializer
-
Load a MultiLayerNetwork from InputStream from an input stream
Note: the input stream is read fully and closed by this method.
- restoreMultiLayerNetwork(InputStream) - Static method in class org.deeplearning4j.util.ModelSerializer
-
Restore a multi layer network from an input stream
* Note: the input stream is read fully and closed by this method.
- restoreMultiLayerNetwork(String) - Static method in class org.deeplearning4j.util.ModelSerializer
-
Load a MultilayerNetwork model from a file
- restoreMultiLayerNetwork(String, boolean) - Static method in class org.deeplearning4j.util.ModelSerializer
-
Load a MultilayerNetwork model from a file
- restoreMultiLayerNetworkAndNormalizer(InputStream, boolean) - Static method in class org.deeplearning4j.util.ModelSerializer
-
Restore a MultiLayerNetwork and Normalizer (if present - null if not) from the InputStream.
- restoreMultiLayerNetworkAndNormalizer(File, boolean) - Static method in class org.deeplearning4j.util.ModelSerializer
-
Restore a MultiLayerNetwork and Normalizer (if present - null if not) from a File
- restoreNormalizerFromFile(File) - Static method in class org.deeplearning4j.util.ModelSerializer
-
This method restores normalizer from a given persisted model file
PLEASE NOTE: File should be model file saved earlier with ModelSerializer with addNormalizerToModel being called
- restoreNormalizerFromInputStream(InputStream) - Static method in class org.deeplearning4j.util.ModelSerializer
-
This method restores the normalizer form a persisted model file.
- Result - Class in org.ansj.domain
-
分词结果的一个封装
- Result(List<Term>) - Constructor for class org.ansj.domain.Result
-
- retainAll(Collection<?>) - Method in class org.deeplearning4j.optimize.solvers.accumulation.FancyBlockingQueue
-
- retainAll(Collection<?>) - Method in class org.deeplearning4j.parallelism.ConcurrentHashSet
-
Deprecated.
- retainAll(Collection<?>) - Method in class org.deeplearning4j.parallelism.MagicQueue
-
Deprecated.
This method isn't supported
- retainAll(Collection<?>) - Method in class org.deeplearning4j.util.DiskBasedQueue
-
- retentionDelay - Variable in class org.deeplearning4j.models.word2vec.wordstore.inmemory.AbstractCache.Builder
-
- retrieve() - Method in class org.deeplearning4j.text.uima.UimaResource
-
- returnSequences - Variable in class org.deeplearning4j.nn.modelimport.keras.layers.recurrent.KerasLstm
-
- returnSequences - Variable in class org.deeplearning4j.nn.modelimport.keras.layers.recurrent.KerasSimpleRnn
-
- reverse() - Method in class org.deeplearning4j.spark.ordering.DataSetOrdering
-
- reverseTimeSeries(INDArray) - Static method in class org.deeplearning4j.util.TimeSeriesUtils
-
Reverse an input time series along the time dimension
- reverseTimeSeries(INDArray, LayerWorkspaceMgr, ArrayType) - Static method in class org.deeplearning4j.util.TimeSeriesUtils
-
Reverse an input time series along the time dimension
- reverseTimeSeriesMask(INDArray) - Static method in class org.deeplearning4j.util.TimeSeriesUtils
-
Reverse a (per time step) time series mask, with shape [minibatch, timeSeriesLength]
- reverseTimeSeriesMask(INDArray, LayerWorkspaceMgr, ArrayType) - Static method in class org.deeplearning4j.util.TimeSeriesUtils
-
Reverse a (per time step) time series mask, with shape [minibatch, timeSeriesLength]
- ReverseTimeSeriesVertex - Class in org.deeplearning4j.nn.conf.graph.rnn
-
ReverseTimeSeriesVertex is used in recurrent neural networks to revert the order of time series.
- ReverseTimeSeriesVertex() - Constructor for class org.deeplearning4j.nn.conf.graph.rnn.ReverseTimeSeriesVertex
-
Creates a new ReverseTimeSeriesVertex that doesn't pay attention to masks
- ReverseTimeSeriesVertex(String) - Constructor for class org.deeplearning4j.nn.conf.graph.rnn.ReverseTimeSeriesVertex
-
Creates a new ReverseTimeSeriesVertex that uses the mask array of a given input
- ReverseTimeSeriesVertex - Class in org.deeplearning4j.nn.graph.vertex.impl.rnn
-
ReverseTimeSeriesVertex is used in recurrent neural networks to revert the order of time series.
- ReverseTimeSeriesVertex(ComputationGraph, String, int, String) - Constructor for class org.deeplearning4j.nn.graph.vertex.impl.rnn.ReverseTimeSeriesVertex
-
- RIGHT_ID - Static variable in class com.atilika.kuromoji.dict.DictionaryField
-
- rightId - Variable in class com.atilika.kuromoji.dict.DictionaryEntryBase
-
- rightId(short) - Method in class com.atilika.kuromoji.dict.GenericDictionaryEntry.Builder
-
- rmLittlePath() - Method in class org.ansj.util.Graph
-
删除最短的节点
- rmLittlePathByScore() - Method in class org.ansj.util.Graph
-
删除小节点。保证被删除的小节点的单个分数小于等于大节点的分数
- rmLittleSinglePath() - Method in class org.ansj.util.Graph
-
删除无意义的节点,防止viterbi太多
- rng - Variable in class org.deeplearning4j.datasets.fetchers.MnistDataFetcher
-
- rng - Variable in class org.deeplearning4j.datasets.iterator.file.BaseFileIterator
-
- rng - Variable in class org.deeplearning4j.models.embeddings.inmemory.InMemoryLookupTable
-
- rng - Variable in class org.deeplearning4j.models.sequencevectors.graph.walkers.impl.NearestVertexWalker
-
- rng - Variable in class org.deeplearning4j.models.sequencevectors.graph.walkers.impl.RandomWalker
-
- rng - Variable in class org.deeplearning4j.spark.impl.paramavg.BaseTrainingMaster
-
- rng - Variable in class org.deeplearning4j.spark.parameterserver.training.SharedTrainingMaster
-
- rngSeed - Variable in class org.deeplearning4j.spark.impl.paramavg.ParameterAveragingTrainingMaster.Builder
-
- rngSeed(long) - Method in class org.deeplearning4j.spark.impl.paramavg.ParameterAveragingTrainingMaster.Builder
-
Random number generator seed, used mainly for enforcing repeatable splitting on RDDs
Default: no seed set (i.e., random seed)
- rngSeed - Variable in class org.deeplearning4j.spark.parameterserver.training.SharedTrainingMaster.Builder
-
- rngSeed(long) - Method in class org.deeplearning4j.spark.parameterserver.training.SharedTrainingMaster.Builder
-
Random number generator seed, used mainly for enforcing repeatable splitting on RDDs
Default: no seed set (i.e., random seed)
- RNN_MODE - Static variable in class org.deeplearning4j.nn.layers.recurrent.CudnnLSTMHelper
-
- rnnActivateUsingStoredState(INDArray, boolean, boolean, LayerWorkspaceMgr) - Method in interface org.deeplearning4j.nn.api.layers.RecurrentLayer
-
Similar to rnnTimeStep, this method is used for activations using the state
stored in the stateMap as the initialization.
- rnnActivateUsingStoredState(INDArray[], boolean, boolean) - Method in class org.deeplearning4j.nn.graph.ComputationGraph
-
Similar to rnnTimeStep and feedForward() methods.
- rnnActivateUsingStoredState(INDArray, boolean, boolean, LayerWorkspaceMgr) - Method in class org.deeplearning4j.nn.layers.recurrent.BidirectionalLayer
-
- rnnActivateUsingStoredState(INDArray, boolean, boolean, LayerWorkspaceMgr) - Method in class org.deeplearning4j.nn.layers.recurrent.GravesBidirectionalLSTM
-
- rnnActivateUsingStoredState(INDArray, boolean, boolean, LayerWorkspaceMgr) - Method in class org.deeplearning4j.nn.layers.recurrent.GravesLSTM
-
- rnnActivateUsingStoredState(INDArray, boolean, boolean, LayerWorkspaceMgr) - Method in class org.deeplearning4j.nn.layers.recurrent.LSTM
-
- rnnActivateUsingStoredState(INDArray, boolean, boolean, LayerWorkspaceMgr) - Method in class org.deeplearning4j.nn.layers.recurrent.SimpleRnn
-
- rnnActivateUsingStoredState(INDArray, boolean, boolean) - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
-
Similar to rnnTimeStep and feedForward() methods.
- rnnClearPreviousState() - Method in interface org.deeplearning4j.nn.api.layers.RecurrentLayer
-
Reset/clear the stateMap for rnnTimeStep() and tBpttStateMap for rnnActivateUsingStoredState()
- rnnClearPreviousState() - Method in class org.deeplearning4j.nn.graph.ComputationGraph
-
- rnnClearPreviousState() - Method in class org.deeplearning4j.nn.layers.recurrent.BaseRecurrentLayer
-
Reset/clear the stateMap for rnnTimeStep() and tBpttStateMap for rnnActivateUsingStoredState()
- rnnClearPreviousState() - Method in class org.deeplearning4j.nn.layers.recurrent.BidirectionalLayer
-
- rnnClearPreviousState() - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
-
Clear the previous state of the RNN layers (if any).
- rnnGetPreviousState() - Method in interface org.deeplearning4j.nn.api.layers.RecurrentLayer
-
Returns a shallow copy of the RNN stateMap (that contains the stored history for use in methods such
as rnnTimeStep
- rnnGetPreviousState(int) - Method in class org.deeplearning4j.nn.graph.ComputationGraph
-
- rnnGetPreviousState(String) - Method in class org.deeplearning4j.nn.graph.ComputationGraph
-
- rnnGetPreviousState() - Method in class org.deeplearning4j.nn.layers.recurrent.BaseRecurrentLayer
-
Returns a shallow copy of the stateMap
- rnnGetPreviousState() - Method in class org.deeplearning4j.nn.layers.recurrent.BidirectionalLayer
-
- rnnGetPreviousState(int) - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
-
Get the state of the RNN layer, as used in rnnTimeStep().
- rnnGetPreviousStates() - Method in class org.deeplearning4j.nn.graph.ComputationGraph
-
- rnnGetTBPTTState() - Method in interface org.deeplearning4j.nn.api.layers.RecurrentLayer
-
Get the RNN truncated backpropagations through time (TBPTT) state for the recurrent layer.
- rnnGetTBPTTState() - Method in class org.deeplearning4j.nn.layers.recurrent.BaseRecurrentLayer
-
- rnnGetTBPTTState() - Method in class org.deeplearning4j.nn.layers.recurrent.BidirectionalLayer
-
- rnnLayer(Layer) - Method in class org.deeplearning4j.nn.conf.layers.recurrent.Bidirectional.Builder
-
- RnnLossLayer - Class in org.deeplearning4j.nn.conf.layers
-
Recurrent Neural Network Loss Layer.
Handles calculation of gradients etc for various objective functions.
NOTE: Unlike
RnnOutputLayer this RnnLossLayer does not have any parameters - i.e., there is no time
distributed dense component here.
- RnnLossLayer - Class in org.deeplearning4j.nn.layers.recurrent
-
Recurrent Neural Network Loss Layer.
Handles calculation of gradients etc for various objective functions.
NOTE: Unlike
RnnOutputLayer this RnnLossLayer does not have any parameters - i.e., there is no time
distributed dense component here.
- RnnLossLayer(NeuralNetConfiguration) - Constructor for class org.deeplearning4j.nn.layers.recurrent.RnnLossLayer
-
- RnnLossLayer.Builder - Class in org.deeplearning4j.nn.conf.layers
-
- RnnOutputLayer - Class in org.deeplearning4j.nn.conf.layers
-
- RnnOutputLayer - Class in org.deeplearning4j.nn.layers.recurrent
-
Recurrent Neural Network Output Layer.
Handles calculation of gradients etc for various objective functions.
Functionally the same as OutputLayer, but handles output and label reshaping
automatically.
Input and output activations are same as other RNN layers: 3 dimensions with shape
[miniBatchSize,nIn,timeSeriesLength] and [miniBatchSize,nOut,timeSeriesLength] respectively.
- RnnOutputLayer(NeuralNetConfiguration) - Constructor for class org.deeplearning4j.nn.layers.recurrent.RnnOutputLayer
-
- RnnOutputLayer(NeuralNetConfiguration, INDArray) - Constructor for class org.deeplearning4j.nn.layers.recurrent.RnnOutputLayer
-
- RnnOutputLayer.Builder - Class in org.deeplearning4j.nn.conf.layers
-
- rnnSetPreviousState(Map<String, INDArray>) - Method in interface org.deeplearning4j.nn.api.layers.RecurrentLayer
-
Set the stateMap (stored history).
- rnnSetPreviousState(int, Map<String, INDArray>) - Method in class org.deeplearning4j.nn.graph.ComputationGraph
-
- rnnSetPreviousState(String, Map<String, INDArray>) - Method in class org.deeplearning4j.nn.graph.ComputationGraph
-
- rnnSetPreviousState(Map<String, INDArray>) - Method in class org.deeplearning4j.nn.layers.recurrent.BaseRecurrentLayer
-
Set the state map.
- rnnSetPreviousState(Map<String, INDArray>) - Method in class org.deeplearning4j.nn.layers.recurrent.BidirectionalLayer
-
- rnnSetPreviousState(int, Map<String, INDArray>) - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
-
Set the state of the RNN layer.
- rnnSetPreviousStates(Map<String, Map<String, INDArray>>) - Method in class org.deeplearning4j.nn.graph.ComputationGraph
-
- rnnSetTBPTTState(Map<String, INDArray>) - Method in interface org.deeplearning4j.nn.api.layers.RecurrentLayer
-
Set the RNN truncated backpropagations through time (TBPTT) state for the recurrent layer.
- rnnSetTBPTTState(Map<String, INDArray>) - Method in class org.deeplearning4j.nn.layers.recurrent.BaseRecurrentLayer
-
- rnnSetTBPTTState(Map<String, INDArray>) - Method in class org.deeplearning4j.nn.layers.recurrent.BidirectionalLayer
-
- rnnTimeStep(INDArray, LayerWorkspaceMgr) - Method in interface org.deeplearning4j.nn.api.layers.RecurrentLayer
-
Do one or more time steps using the previous time step state stored in stateMap.
Can be used to efficiently do forward pass one or n-steps at a time (instead of doing
forward pass always from t=0)
If stateMap is empty, default initialization (usually zeros) is used
Implementations also update stateMap at the end of this method
- rnnTimeStep(INDArray...) - Method in class org.deeplearning4j.nn.graph.ComputationGraph
-
If this ComputationGraph contains one or more RNN layers: conduct forward pass (prediction)
but using previous stored state for any RNN layers.
- rnnTimeStep(INDArray, LayerWorkspaceMgr) - Method in class org.deeplearning4j.nn.layers.recurrent.BidirectionalLayer
-
- rnnTimeStep(INDArray, LayerWorkspaceMgr) - Method in class org.deeplearning4j.nn.layers.recurrent.GravesBidirectionalLSTM
-
- rnnTimeStep(INDArray, LayerWorkspaceMgr) - Method in class org.deeplearning4j.nn.layers.recurrent.GravesLSTM
-
- rnnTimeStep(INDArray, LayerWorkspaceMgr) - Method in class org.deeplearning4j.nn.layers.recurrent.LSTM
-
- rnnTimeStep(INDArray, LayerWorkspaceMgr) - Method in class org.deeplearning4j.nn.layers.recurrent.SimpleRnn
-
- rnnTimeStep(INDArray) - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
-
If this MultiLayerNetwork contains one or more RNN layers: conduct forward pass (prediction)
but using previous stored state for any RNN layers.
- RnnToCnnPreProcessor - Class in org.deeplearning4j.nn.conf.preprocessor
-
A preprocessor to allow RNN and CNN layers to be used together
For example, time series (video) input -> ConvolutionLayer, or conceivable GravesLSTM -> ConvolutionLayer
Functionally equivalent to combining RnnToFeedForwardPreProcessor + FeedForwardToCnnPreProcessor
Specifically, this does two things:
(a) Reshape 3d activations out of RNN layer, with shape [miniBatchSize, numChannels*inputHeight*inputWidth, timeSeriesLength])
into 4d (CNN) activations (with shape [numExamples*timeSeriesLength, numChannels, inputWidth, inputHeight])
(b) Reshapes 4d epsilons (weights.*deltas) out of CNN layer (with shape
[numExamples*timeSeriesLength, numChannels, inputHeight, inputWidth]) into 3d epsilons with shape
[miniBatchSize, numChannels*inputHeight*inputWidth, timeSeriesLength] suitable to feed into CNN layers.
- RnnToCnnPreProcessor(int, int, int) - Constructor for class org.deeplearning4j.nn.conf.preprocessor.RnnToCnnPreProcessor
-
- RnnToFeedForwardPreProcessor - Class in org.deeplearning4j.nn.conf.preprocessor
-
A preprocessor to allow RNN and feed-forward network layers to be used together.
For example, GravesLSTM -> OutputLayer or GravesLSTM -> DenseLayer
This does two things:
(a) Reshapes activations out of RNN layer (which is 3D with shape
[miniBatchSize,layerSize,timeSeriesLength]) into 2d activations (with shape
[miniBatchSize*timeSeriesLength,layerSize]) suitable for use in feed-forward layers.
(b) Reshapes 2d epsilons (weights*deltas from feed forward layer, with shape
[miniBatchSize*timeSeriesLength,layerSize]) into 3d epsilons (with shape
[miniBatchSize,layerSize,timeSeriesLength]) for use in RNN layer
- RnnToFeedForwardPreProcessor() - Constructor for class org.deeplearning4j.nn.conf.preprocessor.RnnToFeedForwardPreProcessor
-
- rnnUpdateStateWithTBPTTState() - Method in class org.deeplearning4j.nn.graph.ComputationGraph
-
Update the internal state of RNN layers after a truncated BPTT fit call
- ROC - Class in org.deeplearning4j.eval
-
ROC (Receiver Operating Characteristic) for binary classifiers.
ROC has 2 modes of operation:
(a) Thresholded (less memory)
(b) Exact (default; use numSteps == 0 to set.
- ROC() - Constructor for class org.deeplearning4j.eval.ROC
-
- ROC(int) - Constructor for class org.deeplearning4j.eval.ROC
-
- ROC(int, boolean) - Constructor for class org.deeplearning4j.eval.ROC
-
- ROC(int, boolean, int) - Constructor for class org.deeplearning4j.eval.ROC
-
- ROC.CountsForThreshold - Class in org.deeplearning4j.eval
-
- ROCArraySerializer - Class in org.deeplearning4j.eval.serde
-
Custom Jackson serializer for ROC[].
- ROCArraySerializer() - Constructor for class org.deeplearning4j.eval.serde.ROCArraySerializer
-
- ROCBinary - Class in org.deeplearning4j.eval
-
ROC (Receiver Operating Characteristic) for multi-task binary classifiers.
- ROCBinary() - Constructor for class org.deeplearning4j.eval.ROCBinary
-
- ROCBinary(int) - Constructor for class org.deeplearning4j.eval.ROCBinary
-
- ROCBinary(int, boolean) - Constructor for class org.deeplearning4j.eval.ROCBinary
-
- rocChartToHtml(ROC) - Static method in class org.deeplearning4j.evaluation.EvaluationTools
-
Given a
ROC instance, render the ROC chart and precision vs.
- rocChartToHtml(ROCMultiClass) - Static method in class org.deeplearning4j.evaluation.EvaluationTools
-
Given a
ROCMultiClass instance, render the ROC chart and precision vs.
- rocChartToHtml(ROCMultiClass, List<String>) - Static method in class org.deeplearning4j.evaluation.EvaluationTools
-
Given a
ROCMultiClass instance and (optionally) names for each class, render the ROC chart to a stand-alone
HTML file (returned as a String)
- RocCurve - Class in org.deeplearning4j.eval.curves
-
ROC curve: a set of (false positive, true positive) tuples at different thresholds
- RocCurve(double[], double[], double[]) - Constructor for class org.deeplearning4j.eval.curves.RocCurve
-
- ROCMultiClass - Class in org.deeplearning4j.eval
-
ROC (Receiver Operating Characteristic) for multi-class classifiers.
- ROCMultiClass() - Constructor for class org.deeplearning4j.eval.ROCMultiClass
-
- ROCMultiClass(int) - Constructor for class org.deeplearning4j.eval.ROCMultiClass
-
- ROCMultiClass(int, boolean) - Constructor for class org.deeplearning4j.eval.ROCMultiClass
-
- ROCScoreCalculator - Class in org.deeplearning4j.earlystopping.scorecalc
-
Calculate ROC AUC (area under ROC curve) or AUCPR (area under precision recall curve) for a MultiLayerNetwork or
ComputationGraph
- ROCScoreCalculator(ROCScoreCalculator.ROCType, DataSetIterator) - Constructor for class org.deeplearning4j.earlystopping.scorecalc.ROCScoreCalculator
-
- ROCScoreCalculator(ROCScoreCalculator.ROCType, MultiDataSetIterator) - Constructor for class org.deeplearning4j.earlystopping.scorecalc.ROCScoreCalculator
-
- ROCScoreCalculator(ROCScoreCalculator.ROCType, ROCScoreCalculator.Metric, DataSetIterator) - Constructor for class org.deeplearning4j.earlystopping.scorecalc.ROCScoreCalculator
-
- ROCScoreCalculator(ROCScoreCalculator.ROCType, ROCScoreCalculator.Metric, MultiDataSetIterator) - Constructor for class org.deeplearning4j.earlystopping.scorecalc.ROCScoreCalculator
-
- ROCScoreCalculator.Metric - Enum in org.deeplearning4j.earlystopping.scorecalc
-
- ROCScoreCalculator.ROCType - Enum in org.deeplearning4j.earlystopping.scorecalc
-
- ROCSerializer - Class in org.deeplearning4j.eval.serde
-
Custom Jackson serializer for ROC.
- ROCSerializer() - Constructor for class org.deeplearning4j.eval.serde.ROCSerializer
-
- root - Variable in class com.atilika.kuromoji.trie.PatriciaTrie
-
Root value is left -- right is unused
- root - Variable in class org.ansj.util.Graph
-
- ROOT_CACHE_DIR - Static variable in class org.deeplearning4j.datasets.fetchers.CacheableExtractableDataSetFetcher
-
- ROOT_CACHE_DIR - Static variable in class org.deeplearning4j.zoo.ZooModel
-
- rootFolder - Variable in class org.deeplearning4j.optimize.listeners.callbacks.ModelSavingCallback
-
- rootMeanSquaredError(int) - Method in class org.deeplearning4j.eval.RegressionEvaluation
-
- rootMeansSquaredError(double[], double[]) - Static method in class org.deeplearning4j.clustering.util.MathUtils
-
This returns the root mean squared error of two data sets
- round(double) - Static method in class org.deeplearning4j.clustering.util.MathUtils
-
Rounds a double to the next nearest integer value.
- RoundCount - Class in org.deeplearning4j.models.glove.count
-
Simple circular counter, that circulates within 0...Limit, both inclusive
- RoundCount(int) - Constructor for class org.deeplearning4j.models.glove.count.RoundCount
-
Creates new RoundCount instance.
- RoundCount(int, int) - Constructor for class org.deeplearning4j.models.glove.count.RoundCount
-
Creates new RoundCount instance.
- roundDouble(double, int) - Static method in class org.deeplearning4j.clustering.util.MathUtils
-
Rounds a double to the given number of decimal places.
- roundFloat(float, int) - Static method in class org.deeplearning4j.clustering.util.MathUtils
-
Rounds a double to the given number of decimal places.
- Route - Class in org.deeplearning4j.ui.api
-
A Route specifies an endpoint that can be queried in the UI - along with how it should be handled
- Route(String, HttpMethod, FunctionType, Supplier<Result>) - Constructor for class org.deeplearning4j.ui.api.Route
-
- Route(String, HttpMethod, FunctionType, Function<String, Result>) - Constructor for class org.deeplearning4j.ui.api.Route
-
- Route(String, HttpMethod, FunctionType, BiFunction<String, String, Result>) - Constructor for class org.deeplearning4j.ui.api.Route
-
- RoutingIterationListener - Interface in org.deeplearning4j.api.storage.listener
-
- RPForest - Class in org.deeplearning4j.clustering.randomprojection
-
- RPForest(int, int, String) - Constructor for class org.deeplearning4j.clustering.randomprojection.RPForest
-
Create the rp forest with the specified number of trees
- RPHyperPlanes - Class in org.deeplearning4j.clustering.randomprojection
-
- RPHyperPlanes(int) - Constructor for class org.deeplearning4j.clustering.randomprojection.RPHyperPlanes
-
- RPNode - Class in org.deeplearning4j.clustering.randomprojection
-
- RPNode(RPTree, int) - Constructor for class org.deeplearning4j.clustering.randomprojection.RPNode
-
- RPTree - Class in org.deeplearning4j.clustering.randomprojection
-
- RPTree(int, int, String) - Constructor for class org.deeplearning4j.clustering.randomprojection.RPTree
-
- RPTree(int, int) - Constructor for class org.deeplearning4j.clustering.randomprojection.RPTree
-
- RPUtils - Class in org.deeplearning4j.clustering.randomprojection
-
A port of:
https://github.com/lyst/rpforest
to nd4j
- RPUtils() - Constructor for class org.deeplearning4j.clustering.randomprojection.RPUtils
-
- RRMDSIFunction - Class in org.deeplearning4j.spark.datavec.iterator
-
- RRMDSIFunction() - Constructor for class org.deeplearning4j.spark.datavec.iterator.RRMDSIFunction
-
- rSquared(int) - Method in class org.deeplearning4j.eval.RegressionEvaluation
-
Coefficient of Determination (R^2 Score)
- run() - Method in class org.deeplearning4j.datasets.iterator.AsyncDataSetIterator.AsyncPrefetchThread
-
- run() - Method in class org.deeplearning4j.datasets.iterator.AsyncMultiDataSetIterator.AsyncPrefetchThread
-
- run() - Method in class org.deeplearning4j.models.sequencevectors.SequenceVectors.AsyncSequencer
-
- run() - Method in class org.deeplearning4j.models.word2vec.wordstore.VocabConstructor.VocabRunnable
-
- run() - Method in class org.deeplearning4j.parallelism.main.ParallelWrapperMain
-
- run() - Method in class org.deeplearning4j.parallelism.trainer.DefaultTrainer
-
- run() - Method in class org.deeplearning4j.perf.listener.SystemPolling
-
- run(SharedTrainingWorker) - Method in class org.deeplearning4j.spark.parameterserver.pw.SharedTrainingWrapper
-
- runHelper() - Method in class org.deeplearning4j.nearestneighbor.server.NearestNeighborsServer
-
- runMain(String...) - Method in class org.deeplearning4j.nearestneighbor.server.NearestNeighborsServer
-
- runMain(String...) - Method in class org.deeplearning4j.parallelism.main.ParallelWrapperMain
-
- runMain(String[]) - Method in class org.deeplearning4j.ui.play.PlayUIServer
-
- running(AtomicInteger) - Method in class org.deeplearning4j.parallelism.parameterserver.ParameterServerTrainer.ParameterServerTrainerBuilder
-
- running - Variable in class org.deeplearning4j.parallelism.trainer.DefaultTrainer
-
- runRemoteCommand(String) - Method in class org.deeplearning4j.aws.ec2.provision.HostProvisioner
-
- S - Static variable in class org.ansj.app.crf.Config
-
- S3Downloader - Class in org.deeplearning4j.aws.s3.reader
-
Downloads files from S3
- S3Downloader() - Constructor for class org.deeplearning4j.aws.s3.reader.S3Downloader
-
- s3JarFolder(String) - Method in class org.deeplearning4j.aws.emr.SparkEMRClient.Builder
-
the S3 folder in which to find the application jar
- S3Uploader - Class in org.deeplearning4j.aws.s3.uploader
-
Uploads files to S3
- S3Uploader() - Constructor for class org.deeplearning4j.aws.s3.uploader.S3Uploader
-
- sameDiff - Variable in class org.deeplearning4j.nn.layers.samediff.SameDiffLayer
-
- SameDiffLayer - Class in org.deeplearning4j.nn.layers.samediff
-
- SameDiffLayer(NeuralNetConfiguration) - Constructor for class org.deeplearning4j.nn.layers.samediff.SameDiffLayer
-
- SameDiffLayerUtils - Class in org.deeplearning4j.nn.conf.layers.samediff
-
- SameDiffParamInitializer - Class in org.deeplearning4j.nn.params
-
- SameDiffParamInitializer() - Constructor for class org.deeplearning4j.nn.params.SameDiffParamInitializer
-
- sample - Variable in class org.deeplearning4j.bagofwords.vectorizer.Builder
-
Deprecated.
- sample(double) - Method in class org.deeplearning4j.bagofwords.vectorizer.Builder
-
Deprecated.
- sample() - Method in interface org.deeplearning4j.text.invertedindex.InvertedIndex
-
Sampling for creating mini batches
- sampleDoublesInInterval(double[][], int) - Static method in class org.deeplearning4j.clustering.util.MathUtils
-
- sampleHiddenGivenVisible(INDArray) - Method in class org.deeplearning4j.nn.layers.BasePretrainNetwork
-
Sample the hidden distribution given the visible
- sampleHiddenGivenVisible(INDArray) - Method in class org.deeplearning4j.nn.layers.feedforward.autoencoder.AutoEncoder
-
- sampleVisibleGivenHidden(INDArray) - Method in class org.deeplearning4j.nn.layers.BasePretrainNetwork
-
Sample the visible distribution given the hidden
- sampleVisibleGivenHidden(INDArray) - Method in class org.deeplearning4j.nn.layers.feedforward.autoencoder.AutoEncoder
-
- sampling - Variable in class org.deeplearning4j.models.embeddings.learning.impl.elements.CBOW
-
- sampling - Variable in class org.deeplearning4j.models.embeddings.learning.impl.elements.SkipGram
-
- sampling - Variable in class org.deeplearning4j.models.embeddings.learning.impl.sequence.DM
-
- sampling - Variable in class org.deeplearning4j.models.embeddings.wordvectors.WordVectorsImpl
-
- sampling(double) - Method in class org.deeplearning4j.models.glove.Glove.Builder
-
Deprecated.
- sampling(double) - Method in class org.deeplearning4j.models.node2vec.Node2Vec.Builder
-
Deprecated.
- sampling(double) - Method in class org.deeplearning4j.models.paragraphvectors.ParagraphVectors.Builder
-
This method defines whether subsampling should be used or not
- sampling - Variable in class org.deeplearning4j.models.sequencevectors.SequenceVectors.Builder
-
- sampling(double) - Method in class org.deeplearning4j.models.sequencevectors.SequenceVectors.Builder
-
This method defines sub-sampling threshold.
- sampling(double) - Method in class org.deeplearning4j.models.word2vec.Word2Vec.Builder
-
This method defines whether subsampling should be used or not
- sampling - Variable in class org.deeplearning4j.spark.models.embeddings.word2vec.Word2Vec.Builder
-
- sampling(double) - Method in class org.deeplearning4j.spark.models.embeddings.word2vec.Word2Vec.Builder
-
Specifies subsamplng value
- SamplingDataSetIterator - Class in org.deeplearning4j.datasets.iterator
-
A wrapper for a dataset to sample from.
- SamplingDataSetIterator(DataSet, int, int) - Constructor for class org.deeplearning4j.datasets.iterator.SamplingDataSetIterator
-
- SamplingMode - Enum in org.deeplearning4j.models.sequencevectors.graph.enums
-
- samplingMode - Variable in class org.deeplearning4j.models.sequencevectors.graph.walkers.impl.NearestVertexWalker.Builder
-
- samplingMode - Variable in class org.deeplearning4j.models.sequencevectors.graph.walkers.impl.NearestVertexWalker
-
- save(File) - Method in class org.deeplearning4j.nn.graph.ComputationGraph
-
Save the ComputationGraph to a file.
- save(File, boolean) - Method in class org.deeplearning4j.nn.graph.ComputationGraph
-
Save the ComputationGraph to a file.
- save(File) - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
-
Save the MultiLayerNetwork to a file.
- save(File, boolean) - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
-
Save the MultiLayerNetwork to a file.
- save(Model, String) - Method in class org.deeplearning4j.optimize.listeners.callbacks.ModelSavingCallback
-
This method saves model
- saveAsFile(List<String>, String) - Method in class org.deeplearning4j.plot.BarnesHutTsne
-
Save the model as a file with a csv format, adding the label as the last column.
- saveBestModel(T, double) - Method in interface org.deeplearning4j.earlystopping.EarlyStoppingModelSaver
-
Save the best model (so far) learned during early stopping training
- saveBestModel(T, double) - Method in class org.deeplearning4j.earlystopping.saver.InMemoryModelSaver
-
- saveBestModel(ComputationGraph, double) - Method in class org.deeplearning4j.earlystopping.saver.LocalFileGraphSaver
-
- saveBestModel(MultiLayerNetwork, double) - Method in class org.deeplearning4j.earlystopping.saver.LocalFileModelSaver
-
- saveEvery(long, TimeUnit) - Method in class org.deeplearning4j.optimize.listeners.checkpoint.CheckpointListener.Builder
-
Save a model periodically
- saveEvery(long, TimeUnit, boolean) - Method in class org.deeplearning4j.optimize.listeners.checkpoint.CheckpointListener.Builder
-
Save a model periodically (if sinceLast == false), or if the specified amount of time has elapsed since
the last model was saved (if sinceLast == true)
- saveEveryEpoch() - Method in class org.deeplearning4j.optimize.listeners.checkpoint.CheckpointListener.Builder
-
Save a model at the end of every epoch
- saveEveryNEpochs(int) - Method in class org.deeplearning4j.optimize.listeners.checkpoint.CheckpointListener.Builder
-
Save a model at the end of every N epochs
- saveEveryNIterations(int) - Method in class org.deeplearning4j.optimize.listeners.checkpoint.CheckpointListener.Builder
-
Save a model every N iterations
- saveEveryNIterations(int, boolean) - Method in class org.deeplearning4j.optimize.listeners.checkpoint.CheckpointListener.Builder
-
Save a model every N iterations (if sinceLast == false), or if N iterations have passed since
the last model vas saved (if sinceLast == true)
- saveHTMLFile(String, Component...) - Static method in class org.deeplearning4j.ui.standalone.StaticPageUtil
-
- saveHTMLFile(File, Component...) - Static method in class org.deeplearning4j.ui.standalone.StaticPageUtil
-
- saveLastModel(boolean) - Method in class org.deeplearning4j.earlystopping.EarlyStoppingConfiguration.Builder
-
Save the last model? If true: save the most recent model at each epoch, in addition to the best
model (whenever the best model improves).
- saveLatestModel(T, double) - Method in interface org.deeplearning4j.earlystopping.EarlyStoppingModelSaver
-
Save the latest (most recent) model learned during early stopping
- saveLatestModel(T, double) - Method in class org.deeplearning4j.earlystopping.saver.InMemoryModelSaver
-
- saveLatestModel(ComputationGraph, double) - Method in class org.deeplearning4j.earlystopping.saver.LocalFileGraphSaver
-
- saveLatestModel(MultiLayerNetwork, double) - Method in class org.deeplearning4j.earlystopping.saver.LocalFileModelSaver
-
- saveUpdater - Variable in class org.deeplearning4j.spark.impl.paramavg.ParameterAveragingTrainingMaster.Builder
-
- saveUpdater(boolean) - Method in class org.deeplearning4j.spark.impl.paramavg.ParameterAveragingTrainingMaster.Builder
-
Set whether the updater (i.e., historical state for momentum, adagrad, etc should be saved).
- saveUpdater - Variable in class org.deeplearning4j.spark.impl.paramavg.ParameterAveragingTrainingMaster
-
- saveVocab() - Method in class org.deeplearning4j.models.word2vec.wordstore.inmemory.AbstractCache
-
Serialize vocabulary to specified path
- saveVocab() - Method in class org.deeplearning4j.models.word2vec.wordstore.inmemory.InMemoryLookupCache
-
Deprecated.
- saveVocab() - Method in interface org.deeplearning4j.models.word2vec.wordstore.VocabCache
-
Saves the vocab: this allow for reuse of word frequencies
- sbeBlockLength() - Static method in class org.deeplearning4j.ui.stats.sbe.StaticInfoDecoder.HwDeviceInfoGroupDecoder
-
- sbeBlockLength() - Static method in class org.deeplearning4j.ui.stats.sbe.StaticInfoDecoder.ModelParamNamesDecoder
-
- sbeBlockLength() - Method in class org.deeplearning4j.ui.stats.sbe.StaticInfoDecoder
-
- sbeBlockLength() - Static method in class org.deeplearning4j.ui.stats.sbe.StaticInfoDecoder.SwEnvironmentInfoDecoder
-
- sbeBlockLength() - Static method in class org.deeplearning4j.ui.stats.sbe.StaticInfoEncoder.HwDeviceInfoGroupEncoder
-
- sbeBlockLength() - Static method in class org.deeplearning4j.ui.stats.sbe.StaticInfoEncoder.ModelParamNamesEncoder
-
- sbeBlockLength() - Method in class org.deeplearning4j.ui.stats.sbe.StaticInfoEncoder
-
- sbeBlockLength() - Static method in class org.deeplearning4j.ui.stats.sbe.StaticInfoEncoder.SwEnvironmentInfoEncoder
-
- sbeBlockLength() - Static method in class org.deeplearning4j.ui.stats.sbe.StorageMetaDataDecoder.ExtraMetaDataBytesDecoder
-
- sbeBlockLength() - Method in class org.deeplearning4j.ui.stats.sbe.StorageMetaDataDecoder
-
- sbeBlockLength() - Static method in class org.deeplearning4j.ui.stats.sbe.StorageMetaDataEncoder.ExtraMetaDataBytesEncoder
-
- sbeBlockLength() - Method in class org.deeplearning4j.ui.stats.sbe.StorageMetaDataEncoder
-
- sbeBlockLength() - Static method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder.DataSetMetaDataBytesDecoder.MetaDataBytesDecoder
-
- sbeBlockLength() - Static method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder.DataSetMetaDataBytesDecoder
-
- sbeBlockLength() - Static method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder.GcStatsDecoder
-
- sbeBlockLength() - Static method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder.LayerNamesDecoder
-
- sbeBlockLength() - Static method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder.MemoryUseDecoder
-
- sbeBlockLength() - Static method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder.ParamNamesDecoder
-
- sbeBlockLength() - Static method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder.PerformanceDecoder
-
- sbeBlockLength() - Static method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder.PerParameterStatsDecoder.HistogramsDecoder.HistogramCountsDecoder
-
- sbeBlockLength() - Static method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder.PerParameterStatsDecoder.HistogramsDecoder
-
- sbeBlockLength() - Static method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder.PerParameterStatsDecoder
-
- sbeBlockLength() - Static method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder.PerParameterStatsDecoder.SummaryStatDecoder
-
- sbeBlockLength() - Method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder
-
- sbeBlockLength() - Static method in class org.deeplearning4j.ui.stats.sbe.UpdateEncoder.DataSetMetaDataBytesEncoder.MetaDataBytesEncoder
-
- sbeBlockLength() - Static method in class org.deeplearning4j.ui.stats.sbe.UpdateEncoder.DataSetMetaDataBytesEncoder
-
- sbeBlockLength() - Static method in class org.deeplearning4j.ui.stats.sbe.UpdateEncoder.GcStatsEncoder
-
- sbeBlockLength() - Static method in class org.deeplearning4j.ui.stats.sbe.UpdateEncoder.LayerNamesEncoder
-
- sbeBlockLength() - Static method in class org.deeplearning4j.ui.stats.sbe.UpdateEncoder.MemoryUseEncoder
-
- sbeBlockLength() - Static method in class org.deeplearning4j.ui.stats.sbe.UpdateEncoder.ParamNamesEncoder
-
- sbeBlockLength() - Static method in class org.deeplearning4j.ui.stats.sbe.UpdateEncoder.PerformanceEncoder
-
- sbeBlockLength() - Static method in class org.deeplearning4j.ui.stats.sbe.UpdateEncoder.PerParameterStatsEncoder.HistogramsEncoder.HistogramCountsEncoder
-
- sbeBlockLength() - Static method in class org.deeplearning4j.ui.stats.sbe.UpdateEncoder.PerParameterStatsEncoder.HistogramsEncoder
-
- sbeBlockLength() - Static method in class org.deeplearning4j.ui.stats.sbe.UpdateEncoder.PerParameterStatsEncoder
-
- sbeBlockLength() - Static method in class org.deeplearning4j.ui.stats.sbe.UpdateEncoder.PerParameterStatsEncoder.SummaryStatEncoder
-
- sbeBlockLength() - Method in class org.deeplearning4j.ui.stats.sbe.UpdateEncoder
-
- sbeHeaderSize() - Static method in class org.deeplearning4j.ui.stats.sbe.StaticInfoDecoder.HwDeviceInfoGroupDecoder
-
- sbeHeaderSize() - Static method in class org.deeplearning4j.ui.stats.sbe.StaticInfoDecoder.ModelParamNamesDecoder
-
- sbeHeaderSize() - Static method in class org.deeplearning4j.ui.stats.sbe.StaticInfoDecoder.SwEnvironmentInfoDecoder
-
- sbeHeaderSize() - Static method in class org.deeplearning4j.ui.stats.sbe.StaticInfoEncoder.HwDeviceInfoGroupEncoder
-
- sbeHeaderSize() - Static method in class org.deeplearning4j.ui.stats.sbe.StaticInfoEncoder.ModelParamNamesEncoder
-
- sbeHeaderSize() - Static method in class org.deeplearning4j.ui.stats.sbe.StaticInfoEncoder.SwEnvironmentInfoEncoder
-
- sbeHeaderSize() - Static method in class org.deeplearning4j.ui.stats.sbe.StorageMetaDataDecoder.ExtraMetaDataBytesDecoder
-
- sbeHeaderSize() - Static method in class org.deeplearning4j.ui.stats.sbe.StorageMetaDataEncoder.ExtraMetaDataBytesEncoder
-
- sbeHeaderSize() - Static method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder.DataSetMetaDataBytesDecoder.MetaDataBytesDecoder
-
- sbeHeaderSize() - Static method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder.DataSetMetaDataBytesDecoder
-
- sbeHeaderSize() - Static method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder.GcStatsDecoder
-
- sbeHeaderSize() - Static method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder.LayerNamesDecoder
-
- sbeHeaderSize() - Static method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder.MemoryUseDecoder
-
- sbeHeaderSize() - Static method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder.ParamNamesDecoder
-
- sbeHeaderSize() - Static method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder.PerformanceDecoder
-
- sbeHeaderSize() - Static method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder.PerParameterStatsDecoder.HistogramsDecoder.HistogramCountsDecoder
-
- sbeHeaderSize() - Static method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder.PerParameterStatsDecoder.HistogramsDecoder
-
- sbeHeaderSize() - Static method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder.PerParameterStatsDecoder
-
- sbeHeaderSize() - Static method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder.PerParameterStatsDecoder.SummaryStatDecoder
-
- sbeHeaderSize() - Static method in class org.deeplearning4j.ui.stats.sbe.UpdateEncoder.DataSetMetaDataBytesEncoder.MetaDataBytesEncoder
-
- sbeHeaderSize() - Static method in class org.deeplearning4j.ui.stats.sbe.UpdateEncoder.DataSetMetaDataBytesEncoder
-
- sbeHeaderSize() - Static method in class org.deeplearning4j.ui.stats.sbe.UpdateEncoder.GcStatsEncoder
-
- sbeHeaderSize() - Static method in class org.deeplearning4j.ui.stats.sbe.UpdateEncoder.LayerNamesEncoder
-
- sbeHeaderSize() - Static method in class org.deeplearning4j.ui.stats.sbe.UpdateEncoder.MemoryUseEncoder
-
- sbeHeaderSize() - Static method in class org.deeplearning4j.ui.stats.sbe.UpdateEncoder.ParamNamesEncoder
-
- sbeHeaderSize() - Static method in class org.deeplearning4j.ui.stats.sbe.UpdateEncoder.PerformanceEncoder
-
- sbeHeaderSize() - Static method in class org.deeplearning4j.ui.stats.sbe.UpdateEncoder.PerParameterStatsEncoder.HistogramsEncoder.HistogramCountsEncoder
-
- sbeHeaderSize() - Static method in class org.deeplearning4j.ui.stats.sbe.UpdateEncoder.PerParameterStatsEncoder.HistogramsEncoder
-
- sbeHeaderSize() - Static method in class org.deeplearning4j.ui.stats.sbe.UpdateEncoder.PerParameterStatsEncoder
-
- sbeHeaderSize() - Static method in class org.deeplearning4j.ui.stats.sbe.UpdateEncoder.PerParameterStatsEncoder.SummaryStatEncoder
-
- sbeSchemaId() - Method in class org.deeplearning4j.ui.stats.sbe.StaticInfoDecoder
-
- sbeSchemaId() - Method in class org.deeplearning4j.ui.stats.sbe.StaticInfoEncoder
-
- sbeSchemaId() - Method in class org.deeplearning4j.ui.stats.sbe.StorageMetaDataDecoder
-
- sbeSchemaId() - Method in class org.deeplearning4j.ui.stats.sbe.StorageMetaDataEncoder
-
- sbeSchemaId() - Method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder
-
- sbeSchemaId() - Method in class org.deeplearning4j.ui.stats.sbe.UpdateEncoder
-
- sbeSchemaVersion() - Method in class org.deeplearning4j.ui.stats.sbe.StaticInfoDecoder
-
- sbeSchemaVersion() - Method in class org.deeplearning4j.ui.stats.sbe.StaticInfoEncoder
-
- sbeSchemaVersion() - Method in class org.deeplearning4j.ui.stats.sbe.StorageMetaDataDecoder
-
- sbeSchemaVersion() - Method in class org.deeplearning4j.ui.stats.sbe.StorageMetaDataEncoder
-
- sbeSchemaVersion() - Method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder
-
- sbeSchemaVersion() - Method in class org.deeplearning4j.ui.stats.sbe.UpdateEncoder
-
- sbeSemanticType() - Method in class org.deeplearning4j.ui.stats.sbe.StaticInfoDecoder
-
- sbeSemanticType() - Method in class org.deeplearning4j.ui.stats.sbe.StaticInfoEncoder
-
- sbeSemanticType() - Method in class org.deeplearning4j.ui.stats.sbe.StorageMetaDataDecoder
-
- sbeSemanticType() - Method in class org.deeplearning4j.ui.stats.sbe.StorageMetaDataEncoder
-
- sbeSemanticType() - Method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder
-
- sbeSemanticType() - Method in class org.deeplearning4j.ui.stats.sbe.UpdateEncoder
-
- SbeStatsInitializationReport - Class in org.deeplearning4j.ui.stats.impl
-
- SbeStatsInitializationReport() - Constructor for class org.deeplearning4j.ui.stats.impl.SbeStatsInitializationReport
-
- SbeStatsReport - Class in org.deeplearning4j.ui.stats.impl
-
An implementation of
StatsReport using Simple Binary Encoding (SBE)
- SbeStatsReport() - Constructor for class org.deeplearning4j.ui.stats.impl.SbeStatsReport
-
- SbeStorageMetaData - Class in org.deeplearning4j.ui.storage.impl
-
SbeStorageMetaData: stores information about a given session: for example, the types of the static and update information.
- SbeStorageMetaData() - Constructor for class org.deeplearning4j.ui.storage.impl.SbeStorageMetaData
-
- SbeStorageMetaData(long, String, String, String, Class<?>, Class<?>) - Constructor for class org.deeplearning4j.ui.storage.impl.SbeStorageMetaData
-
- SbeStorageMetaData(long, String, String, String, String, String) - Constructor for class org.deeplearning4j.ui.storage.impl.SbeStorageMetaData
-
- SbeStorageMetaData(long, String, String, String, String, String, Serializable) - Constructor for class org.deeplearning4j.ui.storage.impl.SbeStorageMetaData
-
- sbeTemplateId() - Method in class org.deeplearning4j.ui.stats.sbe.StaticInfoDecoder
-
- sbeTemplateId() - Method in class org.deeplearning4j.ui.stats.sbe.StaticInfoEncoder
-
- sbeTemplateId() - Method in class org.deeplearning4j.ui.stats.sbe.StorageMetaDataDecoder
-
- sbeTemplateId() - Method in class org.deeplearning4j.ui.stats.sbe.StorageMetaDataEncoder
-
- sbeTemplateId() - Method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder
-
- sbeTemplateId() - Method in class org.deeplearning4j.ui.stats.sbe.UpdateEncoder
-
- SbeUtil - Class in org.deeplearning4j.ui.stats.impl
-
- scale(int) - Method in class org.deeplearning4j.nn.conf.memory.LayerMemoryReport
-
Multiply all memory usage by the specified scaling factor
- scaleFactor - Variable in class org.deeplearning4j.nn.conf.graph.ScaleVertex
-
- ScaleVertex - Class in org.deeplearning4j.nn.conf.graph
-
A ScaleVertex is used to scale the size of activations of a single layer
For example, ResNet activations can be scaled in repeating blocks to keep variance
under control.
- ScaleVertex(double) - Constructor for class org.deeplearning4j.nn.conf.graph.ScaleVertex
-
- ScaleVertex - Class in org.deeplearning4j.nn.graph.vertex.impl
-
A ScaleVertex is used to scale the size of activations of a single layer
For example, ResNet activations can be scaled in repeating blocks to keep variance
under control.
- ScaleVertex(ComputationGraph, String, int, double) - Constructor for class org.deeplearning4j.nn.graph.vertex.impl.ScaleVertex
-
- ScaleVertex(ComputationGraph, String, int, VertexIndices[], VertexIndices[], double) - Constructor for class org.deeplearning4j.nn.graph.vertex.impl.ScaleVertex
-
- scanForLeaves(List<RPNode>, RPTree) - Static method in class org.deeplearning4j.clustering.randomprojection.RPUtils
-
Scan for leaves accumulating
the nodes in the passed in list
- scanForLeaves(List<RPNode>, RPNode) - Static method in class org.deeplearning4j.clustering.randomprojection.RPUtils
-
Scan for leaves accumulating
the nodes in the passed in list
- scavengerActivationThreshold(int) - Method in class org.deeplearning4j.models.word2vec.wordstore.VocabularyHolder.Builder
-
Activation threshold defines, how ofter scavenger will be executed, to throw away low-frequency keywords.
- scavengerRetentionDelay(int) - Method in class org.deeplearning4j.models.word2vec.wordstore.inmemory.AbstractCache.Builder
-
- scavengerRetentionDelay(int) - Method in class org.deeplearning4j.models.word2vec.wordstore.VocabularyHolder.Builder
-
Retention delay defines, how long low-freq word will be kept in vocab, during building.
- scavengerThreshold - Variable in class org.deeplearning4j.models.word2vec.wordstore.inmemory.AbstractCache.Builder
-
- scavengerThreshold(int) - Method in class org.deeplearning4j.models.word2vec.wordstore.inmemory.AbstractCache.Builder
-
- SCHEMA_ID - Static variable in class org.deeplearning4j.ui.stats.sbe.StaticInfoDecoder
-
- SCHEMA_ID - Static variable in class org.deeplearning4j.ui.stats.sbe.StaticInfoEncoder
-
- SCHEMA_ID - Static variable in class org.deeplearning4j.ui.stats.sbe.StorageMetaDataDecoder
-
- SCHEMA_ID - Static variable in class org.deeplearning4j.ui.stats.sbe.StorageMetaDataEncoder
-
- SCHEMA_ID - Static variable in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder
-
- SCHEMA_ID - Static variable in class org.deeplearning4j.ui.stats.sbe.UpdateEncoder
-
- SCHEMA_VERSION - Static variable in class org.deeplearning4j.ui.stats.sbe.StaticInfoDecoder
-
- SCHEMA_VERSION - Static variable in class org.deeplearning4j.ui.stats.sbe.StaticInfoEncoder
-
- SCHEMA_VERSION - Static variable in class org.deeplearning4j.ui.stats.sbe.StorageMetaDataDecoder
-
- SCHEMA_VERSION - Static variable in class org.deeplearning4j.ui.stats.sbe.StorageMetaDataEncoder
-
- SCHEMA_VERSION - Static variable in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder
-
- SCHEMA_VERSION - Static variable in class org.deeplearning4j.ui.stats.sbe.UpdateEncoder
-
- schemaId() - Method in class org.deeplearning4j.ui.stats.sbe.MessageHeaderDecoder
-
- schemaId(int) - Method in class org.deeplearning4j.ui.stats.sbe.MessageHeaderEncoder
-
- schemaIdMaxValue() - Static method in class org.deeplearning4j.ui.stats.sbe.MessageHeaderDecoder
-
- schemaIdMaxValue() - Static method in class org.deeplearning4j.ui.stats.sbe.MessageHeaderEncoder
-
- schemaIdMinValue() - Static method in class org.deeplearning4j.ui.stats.sbe.MessageHeaderDecoder
-
- schemaIdMinValue() - Static method in class org.deeplearning4j.ui.stats.sbe.MessageHeaderEncoder
-
- schemaIdNullValue() - Static method in class org.deeplearning4j.ui.stats.sbe.MessageHeaderDecoder
-
- schemaIdNullValue() - Static method in class org.deeplearning4j.ui.stats.sbe.MessageHeaderEncoder
-
- score() - Method in class org.ansj.domain.Term
-
- score(double) - Method in class org.ansj.domain.Term
-
- score - Variable in class org.ansj.recognition.impl.NatureRecognition.NatureTerm
-
- score() - Method in interface org.deeplearning4j.nn.api.Model
-
The score for the model
- score - Variable in class org.deeplearning4j.nn.graph.ComputationGraph
-
- score(DataSet) - Method in class org.deeplearning4j.nn.graph.ComputationGraph
-
Sets the input and labels and returns a score for the prediction with respect to the true labels
This is equivalent to
ComputationGraph.score(DataSet, boolean) with training==true.
NOTE: this version of the score function can only be used with ComputationGraph networks that have
a single input and a single output.
- score(DataSet, boolean) - Method in class org.deeplearning4j.nn.graph.ComputationGraph
-
Sets the input and labels and returns a score for the prediction with respect to the true labels
NOTE: this version of the score function can only be used with ComputationGraph networks that have
a single input and a single output.
- score(MultiDataSet) - Method in class org.deeplearning4j.nn.graph.ComputationGraph
-
Score the network given the MultiDataSet, at test time
- score(MultiDataSet, boolean) - Method in class org.deeplearning4j.nn.graph.ComputationGraph
-
Sets the input and labels and returns a score for the prediction with respect to the true labels
- score() - Method in class org.deeplearning4j.nn.graph.ComputationGraph
-
- score() - Method in class org.deeplearning4j.nn.layers.AbstractLayer
-
- score - Variable in class org.deeplearning4j.nn.layers.BaseLayer
-
- score() - Method in class org.deeplearning4j.nn.layers.BaseLayer
-
Objective function: the specified objective
- score() - Method in class org.deeplearning4j.nn.layers.convolution.SpaceToBatch
-
- score() - Method in class org.deeplearning4j.nn.layers.convolution.SpaceToDepth
-
- score() - Method in class org.deeplearning4j.nn.layers.convolution.subsampling.Subsampling3DLayer
-
- score() - Method in class org.deeplearning4j.nn.layers.convolution.subsampling.SubsamplingLayer
-
- score() - Method in class org.deeplearning4j.nn.layers.convolution.upsampling.Upsampling2D
-
- score() - Method in class org.deeplearning4j.nn.layers.convolution.upsampling.Upsampling3D
-
- score() - Method in class org.deeplearning4j.nn.layers.objdetect.Yolo2OutputLayer
-
- score() - Method in class org.deeplearning4j.nn.layers.recurrent.BidirectionalLayer
-
- score - Variable in class org.deeplearning4j.nn.layers.variational.VariationalAutoencoder
-
- score() - Method in class org.deeplearning4j.nn.layers.variational.VariationalAutoencoder
-
- score() - Method in class org.deeplearning4j.nn.layers.wrapper.BaseWrapperLayer
-
- score(float[]) - Method in class org.deeplearning4j.nn.modelexport.solr.ltr.model.ScoringModel
-
- score - Variable in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
-
- score(DataSet) - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
-
- score(DataSet, boolean) - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
-
Calculate the score (loss function) of the prediction with respect to the true labels
- score() - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
-
Score of the model (relative to the objective function)
- score() - Method in interface org.deeplearning4j.optimize.api.ConvexOptimizer
-
The score for the optimizer so far
- score - Variable in class org.deeplearning4j.optimize.solvers.BaseOptimizer
-
- score() - Method in class org.deeplearning4j.optimize.solvers.BaseOptimizer
-
- score() - Method in class org.deeplearning4j.plot.BarnesHutTsne
-
- score(String) - Method in class org.deeplearning4j.text.corpora.sentiwordnet.SWN3
-
Scores the text
- score(CAS) - Method in class org.deeplearning4j.text.corpora.sentiwordnet.SWN3
-
- score(Sentence) - Method in class org.deeplearning4j.text.corpora.sentiwordnet.SWN3
-
- score() - Method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder
-
- score(double) - Method in class org.deeplearning4j.ui.stats.sbe.UpdateEncoder
-
- score() - Method in class org.deeplearning4j.ui.stats.sbe.UpdateFieldsPresentDecoder
-
- score(boolean) - Method in class org.deeplearning4j.ui.stats.sbe.UpdateFieldsPresentEncoder
-
- SCORE_KEY - Static variable in class org.deeplearning4j.optimize.solvers.BaseOptimizer
-
- scoreCalculator(ScoreCalculator) - Method in class org.deeplearning4j.earlystopping.EarlyStoppingConfiguration.Builder
-
Score calculator.
- scoreCalculator(Supplier<ScoreCalculator>) - Method in class org.deeplearning4j.earlystopping.EarlyStoppingConfiguration.Builder
-
Score calculator.
- ScoreCalculator<T extends Model> - Interface in org.deeplearning4j.earlystopping.scorecalc
-
ScoreCalculator interface is used to calculate a score for a neural network.
- scoreElements - Variable in class org.deeplearning4j.models.sequencevectors.SequenceVectors
-
- scoreExamples(DataSet, boolean) - Method in class org.deeplearning4j.nn.graph.ComputationGraph
-
Calculate the score for each example in a DataSet individually.
- scoreExamples(MultiDataSet, boolean) - Method in class org.deeplearning4j.nn.graph.ComputationGraph
-
Calculate the score for each example in a DataSet individually.
- scoreExamples(DataSetIterator, boolean) - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
-
- scoreExamples(DataSet, boolean) - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
-
Calculate the score for each example in a DataSet individually.
- scoreExamples(JavaRDD<DataSet>, boolean) - Method in class org.deeplearning4j.spark.impl.graph.SparkComputationGraph
-
- scoreExamples(JavaRDD<DataSet>, boolean, int) - Method in class org.deeplearning4j.spark.impl.graph.SparkComputationGraph
-
- scoreExamples(JavaPairRDD<K, DataSet>, boolean) - Method in class org.deeplearning4j.spark.impl.graph.SparkComputationGraph
-
- scoreExamples(JavaPairRDD<K, DataSet>, boolean, int) - Method in class org.deeplearning4j.spark.impl.graph.SparkComputationGraph
-
- scoreExamples(RDD<DataSet>, boolean) - Method in class org.deeplearning4j.spark.impl.multilayer.SparkDl4jMultiLayer
-
- scoreExamples(JavaRDD<DataSet>, boolean) - Method in class org.deeplearning4j.spark.impl.multilayer.SparkDl4jMultiLayer
-
- scoreExamples(RDD<DataSet>, boolean, int) - Method in class org.deeplearning4j.spark.impl.multilayer.SparkDl4jMultiLayer
-
- scoreExamples(JavaRDD<DataSet>, boolean, int) - Method in class org.deeplearning4j.spark.impl.multilayer.SparkDl4jMultiLayer
-
Score the examples individually, using a specified batch size.
- scoreExamples(JavaPairRDD<K, DataSet>, boolean) - Method in class org.deeplearning4j.spark.impl.multilayer.SparkDl4jMultiLayer
-
- scoreExamples(JavaPairRDD<K, DataSet>, boolean, int) - Method in class org.deeplearning4j.spark.impl.multilayer.SparkDl4jMultiLayer
-
Score the examples individually, using a specified batch size.
- ScoreExamplesFunction - Class in org.deeplearning4j.spark.impl.graph.scoring
-
Function to score examples individually.
- ScoreExamplesFunction(Broadcast<INDArray>, Broadcast<String>, boolean, int) - Constructor for class org.deeplearning4j.spark.impl.graph.scoring.ScoreExamplesFunction
-
- ScoreExamplesFunction - Class in org.deeplearning4j.spark.impl.multilayer.scoring
-
Function to score examples individually.
- ScoreExamplesFunction(Broadcast<INDArray>, Broadcast<String>, boolean, int) - Constructor for class org.deeplearning4j.spark.impl.multilayer.scoring.ScoreExamplesFunction
-
- scoreExamplesMultiDataSet(JavaRDD<MultiDataSet>, boolean) - Method in class org.deeplearning4j.spark.impl.graph.SparkComputationGraph
-
- scoreExamplesMultiDataSet(JavaRDD<MultiDataSet>, boolean, int) - Method in class org.deeplearning4j.spark.impl.graph.SparkComputationGraph
-
Score the examples individually, using a specified batch size.
- scoreExamplesMultiDataSet(JavaPairRDD<K, MultiDataSet>, boolean) - Method in class org.deeplearning4j.spark.impl.graph.SparkComputationGraph
-
- scoreExamplesMultiDataSet(JavaPairRDD<K, MultiDataSet>, boolean, int) - Method in class org.deeplearning4j.spark.impl.graph.SparkComputationGraph
-
Score the examples individually, using a specified batch size.
- ScoreExamplesWithKeyFunction<K> - Class in org.deeplearning4j.spark.impl.graph.scoring
-
Function to score examples individually, where each example is associated with a particular key
Note that scoring is batched for computational efficiency.
This is the Spark implementation of the
ComputationGraph.scoreExamples(MultiDataSet, boolean) method
Note: The MultiDataSet objects passed in must have exactly one example in them (otherwise: can't have a 1:1 association
between keys and data sets to score)
- ScoreExamplesWithKeyFunction(Broadcast<INDArray>, Broadcast<String>, boolean, int) - Constructor for class org.deeplearning4j.spark.impl.graph.scoring.ScoreExamplesWithKeyFunction
-
- ScoreExamplesWithKeyFunction<K> - Class in org.deeplearning4j.spark.impl.multilayer.scoring
-
Function to score examples individually, where each example is associated with a particular key
Note that scoring is batched for computational efficiency.
This is the Spark implementation of t he
MultiLayerNetwork.scoreExamples(DataSet, boolean) method
Note: The DataSet objects passed in must have exactly one example in them (otherwise: can't have a 1:1 association
between keys and data sets to score)
- ScoreExamplesWithKeyFunction(Broadcast<INDArray>, Broadcast<String>, boolean, int) - Constructor for class org.deeplearning4j.spark.impl.multilayer.scoring.ScoreExamplesWithKeyFunction
-
- ScoreFlatMapFunction - Class in org.deeplearning4j.spark.impl.multilayer.scoring
-
- ScoreFlatMapFunction(String, Broadcast<INDArray>, int) - Constructor for class org.deeplearning4j.spark.impl.multilayer.scoring.ScoreFlatMapFunction
-
- ScoreFlatMapFunctionCGDataSet - Class in org.deeplearning4j.spark.impl.graph.scoring
-
Function used to score a DataSet using a ComputationGraph
- ScoreFlatMapFunctionCGDataSet(String, Broadcast<INDArray>, int) - Constructor for class org.deeplearning4j.spark.impl.graph.scoring.ScoreFlatMapFunctionCGDataSet
-
- ScoreFlatMapFunctionCGMultiDataSet - Class in org.deeplearning4j.spark.impl.graph.scoring
-
Function used to score a MultiDataSet using a given ComputationGraph
- ScoreFlatMapFunctionCGMultiDataSet(String, Broadcast<INDArray>, int) - Constructor for class org.deeplearning4j.spark.impl.graph.scoring.ScoreFlatMapFunctionCGMultiDataSet
-
- scoreForMetric(Evaluation.Metric) - Method in class org.deeplearning4j.eval.Evaluation
-
- scoreForMetric(RegressionEvaluation.Metric) - Method in class org.deeplearning4j.eval.RegressionEvaluation
-
- scoreId() - Static method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder
-
- ScoreImprovementEpochTerminationCondition - Class in org.deeplearning4j.earlystopping.termination
-
Terminate training if best model score does not improve for N epochs
- ScoreImprovementEpochTerminationCondition(int) - Constructor for class org.deeplearning4j.earlystopping.termination.ScoreImprovementEpochTerminationCondition
-
- ScoreImprovementEpochTerminationCondition(int, double) - Constructor for class org.deeplearning4j.earlystopping.termination.ScoreImprovementEpochTerminationCondition
-
- ScoreIterationListener - Class in org.deeplearning4j.optimize.listeners
-
Score iteration listener
- ScoreIterationListener(int) - Constructor for class org.deeplearning4j.optimize.listeners.ScoreIterationListener
-
- ScoreIterationListener() - Constructor for class org.deeplearning4j.optimize.listeners.ScoreIterationListener
-
Default constructor printing every 10 iterations
- ScoreListener<T extends SequenceElement> - Class in org.deeplearning4j.models.sequencevectors.listeners
-
Deprecated.
- ScoreListener(ListenerEvent, int) - Constructor for class org.deeplearning4j.models.sequencevectors.listeners.ScoreListener
-
Deprecated.
- scoreMaxValue() - Static method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder
-
- scoreMaxValue() - Static method in class org.deeplearning4j.ui.stats.sbe.UpdateEncoder
-
- scoreMetaAttribute(MetaAttribute) - Static method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder
-
- scoreMinibatch(Model, INDArray, INDArray, INDArray, INDArray, INDArray) - Method in class org.deeplearning4j.earlystopping.scorecalc.AutoencoderScoreCalculator
-
- scoreMinibatch(Model, INDArray[], INDArray[], INDArray[], INDArray[], INDArray[]) - Method in class org.deeplearning4j.earlystopping.scorecalc.AutoencoderScoreCalculator
-
- scoreMinibatch(MultiLayerNetwork, INDArray[], INDArray[], INDArray[], INDArray[], INDArray[]) - Method in class org.deeplearning4j.earlystopping.scorecalc.base.BaseMLNScoreCalculator
-
- scoreMinibatch(T, INDArray, INDArray, INDArray, INDArray, INDArray) - Method in class org.deeplearning4j.earlystopping.scorecalc.base.BaseScoreCalculator
-
- scoreMinibatch(T, INDArray[], INDArray[], INDArray[], INDArray[], INDArray[]) - Method in class org.deeplearning4j.earlystopping.scorecalc.base.BaseScoreCalculator
-
- scoreMinibatch(Model, INDArray[], INDArray[], INDArray[], INDArray[], INDArray[]) - Method in class org.deeplearning4j.earlystopping.scorecalc.DataSetLossCalculator
-
- scoreMinibatch(Model, INDArray, INDArray, INDArray, INDArray, INDArray) - Method in class org.deeplearning4j.earlystopping.scorecalc.VAEReconErrorScoreCalculator
-
- scoreMinibatch(Model, INDArray[], INDArray[], INDArray[], INDArray[], INDArray[]) - Method in class org.deeplearning4j.earlystopping.scorecalc.VAEReconErrorScoreCalculator
-
- scoreMinibatch(Model, INDArray, INDArray, INDArray, INDArray, INDArray) - Method in class org.deeplearning4j.earlystopping.scorecalc.VAEReconProbScoreCalculator
-
- scoreMinibatch(Model, INDArray[], INDArray[], INDArray[], INDArray[], INDArray[]) - Method in class org.deeplearning4j.earlystopping.scorecalc.VAEReconProbScoreCalculator
-
- scoreMinValue() - Static method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder
-
- scoreMinValue() - Static method in class org.deeplearning4j.ui.stats.sbe.UpdateEncoder
-
- scoreNullValue() - Static method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder
-
- scoreNullValue() - Static method in class org.deeplearning4j.ui.stats.sbe.UpdateEncoder
-
- scoreSequences - Variable in class org.deeplearning4j.models.sequencevectors.SequenceVectors
-
- scoreSum - Variable in class org.deeplearning4j.earlystopping.scorecalc.base.BaseScoreCalculator
-
- scoreTokens(List<Token>) - Method in class org.deeplearning4j.text.corpora.sentiwordnet.SWN3
-
- ScoringModel - Class in org.deeplearning4j.nn.modelexport.solr.ltr.model
-
- ScoringModel(String, List<Feature>, List<Normalizer>, String, List<Feature>, Map<String, Object>) - Constructor for class org.deeplearning4j.nn.modelexport.solr.ltr.model.ScoringModel
-
- SDLayerParams - Class in org.deeplearning4j.nn.conf.layers.samediff
-
SDLayerParams is used to define the parameters for a Deeplearning4j SameDiff layer
- SDLayerParams(Map<String, int[]>, Map<String, int[]>) - Constructor for class org.deeplearning4j.nn.conf.layers.samediff.SDLayerParams
-
- search(ViterbiLattice) - Method in class com.atilika.kuromoji.viterbi.ViterbiSearcher
-
Find best path from input lattice.
- search(INDArray, double) - Method in interface org.deeplearning4j.clustering.lsh.LSH
-
Returns the approximate neighbors within a distance bound.
- search(INDArray, int) - Method in interface org.deeplearning4j.clustering.lsh.LSH
-
Returns the approximate neighbors within a k-closest bound
- search(INDArray, double) - Method in class org.deeplearning4j.clustering.lsh.RandomProjectionLSH
-
- search(INDArray, int) - Method in class org.deeplearning4j.clustering.lsh.RandomProjectionLSH
-
- search(INDArray, int, List<DataPoint>, List<Double>) - Method in class org.deeplearning4j.clustering.vptree.VPTree
-
- search(VPTree.Node, INDArray, int, PriorityQueue<HeapObject>, double) - Method in class org.deeplearning4j.clustering.vptree.VPTree
-
- search() - Method in class org.deeplearning4j.clustering.vptree.VPTreeFillSearch
-
- search() - Method in class org.deeplearning4j.nearestneighbor.server.NearestNeighbor
-
- SEARCH_DIR - Static variable in class org.deeplearning4j.optimize.solvers.BaseOptimizer
-
- searchState - Variable in class org.deeplearning4j.optimize.solvers.BaseOptimizer
-
- secondary - Variable in class org.deeplearning4j.optimize.solvers.accumulation.EncodedGradientsAccumulator
-
- secondary - Variable in class org.deeplearning4j.optimize.solvers.accumulation.FancyBlockingQueue
-
- SecondIterationFunction - Class in org.deeplearning4j.spark.models.embeddings.word2vec
-
- SecondIterationFunction(Broadcast<Map<String, Object>>, Broadcast<double[]>, Broadcast<VocabCache<VocabWord>>) - Constructor for class org.deeplearning4j.spark.models.embeddings.word2vec.SecondIterationFunction
-
- secretKey - Variable in class org.deeplearning4j.aws.s3.BaseS3
-
- securityGroupIDs(List<String>) - Method in class org.deeplearning4j.aws.emr.SparkEMRClient.Builder
-
The id of additional security groups this deployment should adopt for both master and slaves
- seed(long) - Method in class org.deeplearning4j.graph.models.deepwalk.DeepWalk.Builder
-
Seed for random number generation (used for repeatability).
- seed - Variable in class org.deeplearning4j.models.embeddings.inmemory.InMemoryLookupTable.Builder
-
- seed(long) - Method in class org.deeplearning4j.models.embeddings.inmemory.InMemoryLookupTable.Builder
-
- seed - Variable in class org.deeplearning4j.models.embeddings.inmemory.InMemoryLookupTable
-
- seed - Variable in class org.deeplearning4j.models.embeddings.wordvectors.WordVectorsImpl
-
- seed(long) - Method in class org.deeplearning4j.models.glove.Glove.Builder
-
- seed(long) - Method in class org.deeplearning4j.models.glove.GloveWeightLookupTable.Builder
-
Deprecated.
- seed(long) - Method in class org.deeplearning4j.models.node2vec.Node2Vec.Builder
-
Deprecated.
- seed(long) - Method in class org.deeplearning4j.models.paragraphvectors.ParagraphVectors.Builder
-
This method defines random seed for random numbers generator
- seed - Variable in class org.deeplearning4j.models.sequencevectors.graph.walkers.impl.NearestVertexWalker.Builder
-
- seed - Variable in class org.deeplearning4j.models.sequencevectors.graph.walkers.impl.NearestVertexWalker
-
- seed - Variable in class org.deeplearning4j.models.sequencevectors.graph.walkers.impl.RandomWalker.Builder
-
- seed - Variable in class org.deeplearning4j.models.sequencevectors.graph.walkers.impl.RandomWalker
-
- seed - Variable in class org.deeplearning4j.models.sequencevectors.SequenceVectors.Builder
-
- seed(long) - Method in class org.deeplearning4j.models.sequencevectors.SequenceVectors.Builder
-
Sets seed for random numbers generator.
- seed(long) - Method in class org.deeplearning4j.models.word2vec.Word2Vec.Builder
-
This method defines random seed for random numbers generator
- seed - Variable in class org.deeplearning4j.nn.conf.NeuralNetConfiguration.Builder
-
- seed(long) - Method in class org.deeplearning4j.nn.conf.NeuralNetConfiguration.Builder
-
Random number generator seed.
- seed - Variable in class org.deeplearning4j.nn.conf.NeuralNetConfiguration
-
- seed(long) - Method in class org.deeplearning4j.nn.transferlearning.FineTuneConfiguration.Builder
-
RNG seed for reproducibility
- seed(int) - Method in class org.deeplearning4j.nn.transferlearning.FineTuneConfiguration.Builder
-
RNG seed for reproducibility
- seed - Variable in class org.deeplearning4j.nn.transferlearning.FineTuneConfiguration
-
- seed - Variable in class org.deeplearning4j.spark.models.embeddings.word2vec.Word2Vec.Builder
-
- seed(long) - Method in class org.deeplearning4j.spark.models.embeddings.word2vec.Word2Vec.Builder
-
Specifies random seed to be used during weights initialization;
- SEED - Static variable in class org.deeplearning4j.spark.models.embeddings.word2vec.Word2VecVariables
-
Deprecated.
- segmenter() - Static method in class org.deeplearning4j.text.sentenceiterator.UimaSentenceIterator
-
Return a sentence segmenter
- selfScore() - Method in class org.ansj.domain.Term
-
- selfScore(double) - Method in class org.ansj.domain.Term
-
- selfScore - Variable in class org.ansj.recognition.impl.NatureRecognition.NatureTerm
-
- sendMessage(INDArray) - Method in class org.deeplearning4j.optimize.solvers.accumulation.EncodingHandler
-
This method does loops encoded data back to updates queue
- sendMessage(INDArray) - Method in class org.deeplearning4j.spark.parameterserver.networking.WiredEncodingHandler
-
This method sends given message to all registered recipients
- Sentence(String) - Constructor for class org.ansj.app.summary.SummaryComputer.Sentence
-
- SentenceAnnotator - Class in org.deeplearning4j.text.annotator
-
- SentenceAnnotator() - Constructor for class org.deeplearning4j.text.annotator.SentenceAnnotator
-
- SentenceBatch - Class in org.deeplearning4j.spark.models.embeddings.word2vec
-
Deprecated.
- SentenceBatch() - Constructor for class org.deeplearning4j.spark.models.embeddings.word2vec.SentenceBatch
-
Deprecated.
- sentenceCounter - Variable in class org.deeplearning4j.models.sequencevectors.transformers.impl.SentenceTransformer
-
- sentenceIter - Variable in class org.deeplearning4j.models.word2vec.Word2Vec
-
- sentenceIterator - Variable in class org.deeplearning4j.bagofwords.vectorizer.Builder
-
Deprecated.
- sentenceIterator - Variable in class org.deeplearning4j.models.glove.Glove.Builder
-
- sentenceIterator - Variable in class org.deeplearning4j.models.word2vec.Word2Vec.Builder
-
- SentenceIterator - Interface in org.deeplearning4j.text.sentenceiterator
-
A sentence iterator that knows how to iterate over sentence.
- SentenceIteratorConverter - Class in org.deeplearning4j.text.sentenceiterator.interoperability
-
Simple class providing compatibility between SentenceIterator/LabelAwareSentenceIterator and LabelAwareIterator
- SentenceIteratorConverter(SentenceIterator) - Constructor for class org.deeplearning4j.text.sentenceiterator.interoperability.SentenceIteratorConverter
-
- SentenceIteratorConverter(SentenceIterator, LabelsSource) - Constructor for class org.deeplearning4j.text.sentenceiterator.interoperability.SentenceIteratorConverter
-
- SentencePreProcessor - Interface in org.deeplearning4j.text.sentenceiterator
-
Sentence pre processor.
- sentenceProvider(LabeledSentenceProvider) - Method in class org.deeplearning4j.iterator.CnnSentenceDataSetIterator.Builder
-
Specify how the (labelled) sentences / documents should be provided
- sentenceProvider(LabelAwareIterator, List<String>) - Method in class org.deeplearning4j.iterator.CnnSentenceDataSetIterator.Builder
-
Specify how the (labelled) sentences / documents should be provided
- sentenceProvider(LabelAwareDocumentIterator, List<String>) - Method in class org.deeplearning4j.iterator.CnnSentenceDataSetIterator.Builder
-
Specify how the (labelled) sentences / documents should be provided
- sentenceProvider(LabelAwareSentenceIterator, List<String>) - Method in class org.deeplearning4j.iterator.CnnSentenceDataSetIterator.Builder
-
Specify how the (labelled) sentences / documents should be provided
- sentences - Variable in class org.deeplearning4j.text.sentenceiterator.UimaResultSetIterator
-
- sentences - Variable in class org.deeplearning4j.text.sentenceiterator.UimaSentenceIterator
-
- sentencesAlongHeight(boolean) - Method in class org.deeplearning4j.iterator.CnnSentenceDataSetIterator.Builder
-
If true (default): output features data with shape [minibatchSize, 1, maxSentenceLength, wordVectorSize]
If false: output features with shape [minibatchSize, 1, wordVectorSize, maxSentenceLength]
- sentenceTransformer - Variable in class org.deeplearning4j.models.sequencevectors.transformers.impl.iterables.BasicTransformerIterator
-
- SentenceTransformer - Class in org.deeplearning4j.models.sequencevectors.transformers.impl
-
This simple class is responsible for conversion lines of text to Sequences of SequenceElements to fit them into SequenceVectors model
- SentenceTransformer.Builder - Class in org.deeplearning4j.models.sequencevectors.transformers.impl
-
- SeparableConvolution2D - Class in org.deeplearning4j.nn.conf.layers
-
2D Separable convolution layer configuration.
- SeparableConvolution2D(SeparableConvolution2D.Builder) - Constructor for class org.deeplearning4j.nn.conf.layers.SeparableConvolution2D
-
SeparableConvolution2D layer
nIn in the input layer is the number of channels
nOut is the number of filters to be used in the net or in other words the channels
The builder specifies the filter/kernel size, the stride and padding
The pooling layer takes the kernel size
- SeparableConvolution2D.Builder - Class in org.deeplearning4j.nn.conf.layers
-
- SeparableConvolution2DLayer - Class in org.deeplearning4j.nn.layers.convolution
-
2D Separable convolution layer implementation
Separable convolutions split a regular convolution operation into two
simpler operations, which are usually computationally more efficient.
- SeparableConvolution2DLayer(NeuralNetConfiguration) - Constructor for class org.deeplearning4j.nn.layers.convolution.SeparableConvolution2DLayer
-
- SeparableConvolution2DLayer(NeuralNetConfiguration, INDArray) - Constructor for class org.deeplearning4j.nn.layers.convolution.SeparableConvolution2DLayer
-
- SeparableConvolutionParamInitializer - Class in org.deeplearning4j.nn.params
-
Initialize separable convolution params.
- SeparableConvolutionParamInitializer() - Constructor for class org.deeplearning4j.nn.params.SeparableConvolutionParamInitializer
-
- sepConvBlock(ComputationGraphConfiguration.GraphBuilder, int, int, int, String, String) - Static method in class org.deeplearning4j.zoo.model.helper.NASNetHelper
-
- Sequence<T extends SequenceElement> - Class in org.deeplearning4j.models.sequencevectors.sequence
-
Sequence for SequenceVectors is defined as limited set of SequenceElements.
- Sequence() - Constructor for class org.deeplearning4j.models.sequencevectors.sequence.Sequence
-
Creates new empty sequence
- Sequence(Collection<T>) - Constructor for class org.deeplearning4j.models.sequencevectors.sequence.Sequence
-
Creates new sequence from collection of elements
- sequenceAlignmentMode(RecordReaderMultiDataSetIterator.AlignmentMode) - Method in class org.deeplearning4j.datasets.datavec.RecordReaderMultiDataSetIterator.Builder
-
Set the sequence alignment mode for all sequences
- SequenceElement - Class in org.deeplearning4j.models.sequencevectors.sequence
-
SequenceElement is basic building block for SequenceVectors.
- SequenceElement() - Constructor for class org.deeplearning4j.models.sequencevectors.sequence.SequenceElement
-
- SequenceElementFactory<T extends SequenceElement> - Interface in org.deeplearning4j.models.sequencevectors.interfaces
-
This is interface for JSON -> SequenceElement serialization/deserialziation
- sequenceId - Variable in class org.deeplearning4j.models.sequencevectors.sequence.Sequence
-
- sequenceIter - Variable in class org.deeplearning4j.datasets.datavec.RecordReaderDataSetIterator
-
- sequenceIterator - Variable in class org.deeplearning4j.models.glove.AbstractCoOccurrences.Builder
-
- sequenceIterator - Variable in class org.deeplearning4j.models.glove.AbstractCoOccurrences
-
- SequenceIterator<T extends SequenceElement> - Interface in org.deeplearning4j.models.sequencevectors.interfaces
-
SequenceIterator is basic interface for learning abstract data that can be represented as sequence of some elements.
- SequenceLearningAlgorithm<T extends SequenceElement> - Interface in org.deeplearning4j.models.embeddings.learning
-
Implementations of this interface should contain sequence-related learning algorithms.
- sequenceLearningAlgorithm(String) - Method in class org.deeplearning4j.models.node2vec.Node2Vec.Builder
-
Deprecated.
- sequenceLearningAlgorithm(SequenceLearningAlgorithm<V>) - Method in class org.deeplearning4j.models.node2vec.Node2Vec.Builder
-
Deprecated.
- sequenceLearningAlgorithm(SequenceLearningAlgorithm<VocabWord>) - Method in class org.deeplearning4j.models.paragraphvectors.ParagraphVectors.Builder
-
- sequenceLearningAlgorithm(String) - Method in class org.deeplearning4j.models.paragraphvectors.ParagraphVectors.Builder
-
- sequenceLearningAlgorithm - Variable in class org.deeplearning4j.models.sequencevectors.SequenceVectors.Builder
-
- sequenceLearningAlgorithm(String) - Method in class org.deeplearning4j.models.sequencevectors.SequenceVectors.Builder
-
Sets specific LearningAlgorithm as Sequence Learning Algorithm
- sequenceLearningAlgorithm(SequenceLearningAlgorithm<T>) - Method in class org.deeplearning4j.models.sequencevectors.SequenceVectors.Builder
-
Sets specific LearningAlgorithm as Sequence Learning Algorithm
- sequenceLearningAlgorithm - Variable in class org.deeplearning4j.models.sequencevectors.SequenceVectors
-
- sequenceLearningAlgorithm - Variable in class org.deeplearning4j.spark.models.sequencevectors.functions.PartitionTrainingFunction
-
- sequenceLearningAlgorithm - Variable in class org.deeplearning4j.spark.models.sequencevectors.functions.TrainingFunction
-
- sequenceLength() - Method in interface org.deeplearning4j.graph.api.IVertexSequence
-
Length of the vertex sequence
- sequenceLength() - Method in class org.deeplearning4j.graph.graph.VertexSequence
-
- sequenceRecord() - Method in class org.deeplearning4j.spark.datavec.iterator.SparkSourceDummySeqReader
-
- sequenceRecord(URI, DataInputStream) - Method in class org.deeplearning4j.spark.datavec.iterator.SparkSourceDummySeqReader
-
- SequenceRecordReaderDataSetIterator - Class in org.deeplearning4j.datasets.datavec
-
Sequence record reader data set iterator
Given a record reader (and optionally another record reader for the labels) generate time series (sequence) data sets.
Supports padding for one-to-many and many-to-one type data loading (i.e., with different number of inputs vs.
- SequenceRecordReaderDataSetIterator(SequenceRecordReader, SequenceRecordReader, int, int) - Constructor for class org.deeplearning4j.datasets.datavec.SequenceRecordReaderDataSetIterator
-
Constructor where features and labels come from different RecordReaders (for example, different files),
and labels are for classification.
- SequenceRecordReaderDataSetIterator(SequenceRecordReader, SequenceRecordReader, int, int, boolean) - Constructor for class org.deeplearning4j.datasets.datavec.SequenceRecordReaderDataSetIterator
-
Constructor where features and labels come from different RecordReaders (for example, different files)
- SequenceRecordReaderDataSetIterator(SequenceRecordReader, SequenceRecordReader, int, int, boolean, SequenceRecordReaderDataSetIterator.AlignmentMode) - Constructor for class org.deeplearning4j.datasets.datavec.SequenceRecordReaderDataSetIterator
-
Constructor where features and labels come from different RecordReaders (for example, different files)
- SequenceRecordReaderDataSetIterator(SequenceRecordReader, int, int, int) - Constructor for class org.deeplearning4j.datasets.datavec.SequenceRecordReaderDataSetIterator
-
Constructor where features and labels come from the SAME RecordReader (i.e., target/label is a column in the
same data as the features).
- SequenceRecordReaderDataSetIterator(SequenceRecordReader, int, int, int, boolean) - Constructor for class org.deeplearning4j.datasets.datavec.SequenceRecordReaderDataSetIterator
-
Constructor where features and labels come from the SAME RecordReader (i.e., target/label is a column in the
same data as the features)
- SequenceRecordReaderDataSetIterator.AlignmentMode - Enum in org.deeplearning4j.datasets.datavec
-
Alignment mode for dealing with input/labels of differing lengths (for example, one-to-many and many-to-one type situations).
- sequencesCount - Variable in class org.deeplearning4j.models.sequencevectors.sequence.SequenceElement
-
- SequenceTransformer<T extends SequenceElement,V> - Interface in org.deeplearning4j.models.sequencevectors.transformers
-
- SequenceVectors<T extends SequenceElement> - Class in org.deeplearning4j.models.sequencevectors
-
SequenceVectors implements abstract features extraction for Sequences and SequenceElements, using SkipGram, CBOW or DBOW (for Sequence features extraction).
- SequenceVectors() - Constructor for class org.deeplearning4j.models.sequencevectors.SequenceVectors
-
- SequenceVectors.AsyncSequencer - Class in org.deeplearning4j.models.sequencevectors
-
This class is used to fetch data from iterator in background thread, and convert it to List
It becomes very usefull if text processing pipeline behind iterator is complex, and we're not loading data from simple text file with whitespaces as separator.
- SequenceVectors.Builder<T extends SequenceElement> - Class in org.deeplearning4j.models.sequencevectors
-
- serialize(ConfusionMatrix<Integer>, JsonGenerator, SerializerProvider) - Method in class org.deeplearning4j.eval.serde.ConfusionMatrixSerializer
-
- serialize(ROC[], JsonGenerator, SerializerProvider) - Method in class org.deeplearning4j.eval.serde.ROCArraySerializer
-
- serialize(ROC, JsonGenerator, SerializerProvider) - Method in class org.deeplearning4j.eval.serde.ROCSerializer
-
- serialize(T) - Method in interface org.deeplearning4j.models.sequencevectors.interfaces.SequenceElementFactory
-
This method serializaes object into JSON string
- serialize(T) - Method in class org.deeplearning4j.models.sequencevectors.serialization.AbstractElementFactory
-
This method serializaes object into JSON string
- serialize(VocabWord) - Method in class org.deeplearning4j.models.sequencevectors.serialization.VocabWordFactory
-
This method serializaes object into JSON string
- serialize(StorageLevel, JsonGenerator, SerializerProvider) - Method in class org.deeplearning4j.spark.util.serde.StorageLevelSerializer
-
- serializeWithType(ROC, JsonGenerator, SerializerProvider, TypeSerializer) - Method in class org.deeplearning4j.eval.serde.ROCSerializer
-
- SerializingListener<T extends SequenceElement> - Class in org.deeplearning4j.models.sequencevectors.listeners
-
This is example VectorsListener implementation.
- SerializingListener() - Constructor for class org.deeplearning4j.models.sequencevectors.listeners.SerializingListener
-
- SerializingListener.Builder<T extends SequenceElement> - Class in org.deeplearning4j.models.sequencevectors.listeners
-
- serialVersionUID - Static variable in class org.deeplearning4j.aws.s3.BaseS3
-
- seriesColors - Variable in class org.deeplearning4j.ui.components.chart.style.StyleChart.Builder
-
- seriesColors(Color...) - Method in class org.deeplearning4j.ui.components.chart.style.StyleChart.Builder
-
- seriesColors(String...) - Method in class org.deeplearning4j.ui.components.chart.style.StyleChart.Builder
-
- seriesColors - Variable in class org.deeplearning4j.ui.components.chart.style.StyleChart
-
- sessionExists(String) - Method in interface org.deeplearning4j.api.storage.StatsStorage
-
Check if the specified session ID exists or not
- sessionExists(String) - Method in class org.deeplearning4j.ui.storage.BaseCollectionStatsStorage
-
- sessionExists(String) - Method in class org.deeplearning4j.ui.storage.sqlite.J7FileStatsStorage
-
- sessionID() - Method in class org.deeplearning4j.ui.stats.sbe.StaticInfoDecoder
-
- sessionID(String) - Method in class org.deeplearning4j.ui.stats.sbe.StaticInfoEncoder
-
- sessionID() - Method in class org.deeplearning4j.ui.stats.sbe.StorageMetaDataDecoder
-
- sessionID(String) - Method in class org.deeplearning4j.ui.stats.sbe.StorageMetaDataEncoder
-
- sessionID() - Method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder
-
- sessionID(String) - Method in class org.deeplearning4j.ui.stats.sbe.UpdateEncoder
-
- sessionIDCharacterEncoding() - Static method in class org.deeplearning4j.ui.stats.sbe.StaticInfoDecoder
-
- sessionIDCharacterEncoding() - Static method in class org.deeplearning4j.ui.stats.sbe.StaticInfoEncoder
-
- sessionIDCharacterEncoding() - Static method in class org.deeplearning4j.ui.stats.sbe.StorageMetaDataDecoder
-
- sessionIDCharacterEncoding() - Static method in class org.deeplearning4j.ui.stats.sbe.StorageMetaDataEncoder
-
- sessionIDCharacterEncoding() - Static method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder
-
- sessionIDCharacterEncoding() - Static method in class org.deeplearning4j.ui.stats.sbe.UpdateEncoder
-
- sessionIDHeaderLength() - Static method in class org.deeplearning4j.ui.stats.sbe.StaticInfoDecoder
-
- sessionIDHeaderLength() - Static method in class org.deeplearning4j.ui.stats.sbe.StaticInfoEncoder
-
- sessionIDHeaderLength() - Static method in class org.deeplearning4j.ui.stats.sbe.StorageMetaDataDecoder
-
- sessionIDHeaderLength() - Static method in class org.deeplearning4j.ui.stats.sbe.StorageMetaDataEncoder
-
- sessionIDHeaderLength() - Static method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder
-
- sessionIDHeaderLength() - Static method in class org.deeplearning4j.ui.stats.sbe.UpdateEncoder
-
- sessionIDId() - Static method in class org.deeplearning4j.ui.stats.sbe.StaticInfoDecoder
-
- sessionIDId() - Static method in class org.deeplearning4j.ui.stats.sbe.StaticInfoEncoder
-
- sessionIDId() - Static method in class org.deeplearning4j.ui.stats.sbe.StorageMetaDataDecoder
-
- sessionIDId() - Static method in class org.deeplearning4j.ui.stats.sbe.StorageMetaDataEncoder
-
- sessionIDId() - Static method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder
-
- sessionIDId() - Static method in class org.deeplearning4j.ui.stats.sbe.UpdateEncoder
-
- sessionIDLength() - Method in class org.deeplearning4j.ui.stats.sbe.StaticInfoDecoder
-
- sessionIDLength() - Method in class org.deeplearning4j.ui.stats.sbe.StorageMetaDataDecoder
-
- sessionIDLength() - Method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder
-
- sessionIDMetaAttribute(MetaAttribute) - Static method in class org.deeplearning4j.ui.stats.sbe.StaticInfoDecoder
-
- sessionIDMetaAttribute(MetaAttribute) - Static method in class org.deeplearning4j.ui.stats.sbe.StaticInfoEncoder
-
- sessionIDMetaAttribute(MetaAttribute) - Static method in class org.deeplearning4j.ui.stats.sbe.StorageMetaDataDecoder
-
- sessionIDMetaAttribute(MetaAttribute) - Static method in class org.deeplearning4j.ui.stats.sbe.StorageMetaDataEncoder
-
- sessionIDMetaAttribute(MetaAttribute) - Static method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder
-
- sessionIDMetaAttribute(MetaAttribute) - Static method in class org.deeplearning4j.ui.stats.sbe.UpdateEncoder
-
- sessionIDs - Variable in class org.deeplearning4j.ui.storage.BaseCollectionStatsStorage
-
- SessionTypeId() - Constructor for class org.deeplearning4j.ui.storage.BaseCollectionStatsStorage.SessionTypeId
-
- SessionTypeWorkerId(String, String, String) - Constructor for class org.deeplearning4j.ui.storage.BaseCollectionStatsStorage.SessionTypeWorkerId
-
- set(int, int) - Method in class com.atilika.kuromoji.compile.WordIdMapCompiler.GrowableIntArray
-
- set(boolean, int) - Method in class org.deeplearning4j.datasets.iterator.parallel.MultiBoolean
-
Sets specified entry to specified state
- setAbsTolx(double) - Method in class org.deeplearning4j.optimize.solvers.BackTrackLineSearch
-
Sets the tolerance of absolute diff in function value.
- setActive(boolean) - Method in class org.ansj.domain.NewWord
-
- setAddress(String) - Method in class org.deeplearning4j.ui.UiConnectionInfo.Builder
-
- setAlpha(double) - Method in class org.deeplearning4j.spark.models.embeddings.word2vec.Word2VecParam.Builder
-
Deprecated.
- setAlpha(double) - Method in class org.deeplearning4j.spark.models.embeddings.word2vec.Word2VecParam
-
Deprecated.
- setAlpha(double) - Method in class org.deeplearning4j.spark.models.embeddings.word2vec.Word2VecPerformerVoid
-
Deprecated.
- setAmbiguityForest(Forest) - Method in class org.ansj.splitWord.Analysis
-
- setAnalysisEngine(AnalysisEngine) - Method in class org.deeplearning4j.text.uima.UimaResource
-
- setAnalysisType(T) - Method in class org.ansj.app.keyword.KeyWordComputer
-
- setBackpropGradientsViewArray(INDArray) - Method in interface org.deeplearning4j.nn.api.Model
-
Set the gradients array as a view of the full (backprop) network parameters
NOTE: this is intended to be used internally in MultiLayerNetwork and ComputationGraph, not by users.
- setBackpropGradientsViewArray(INDArray) - Method in class org.deeplearning4j.nn.graph.ComputationGraph
-
- setBackpropGradientsViewArray(INDArray) - Method in class org.deeplearning4j.nn.graph.vertex.BaseWrapperVertex
-
- setBackpropGradientsViewArray(INDArray) - Method in interface org.deeplearning4j.nn.graph.vertex.GraphVertex
-
- setBackpropGradientsViewArray(INDArray) - Method in class org.deeplearning4j.nn.graph.vertex.impl.ElementWiseVertex
-
- setBackpropGradientsViewArray(INDArray) - Method in class org.deeplearning4j.nn.graph.vertex.impl.InputVertex
-
- setBackpropGradientsViewArray(INDArray) - Method in class org.deeplearning4j.nn.graph.vertex.impl.L2NormalizeVertex
-
- setBackpropGradientsViewArray(INDArray) - Method in class org.deeplearning4j.nn.graph.vertex.impl.L2Vertex
-
- setBackpropGradientsViewArray(INDArray) - Method in class org.deeplearning4j.nn.graph.vertex.impl.LayerVertex
-
- setBackpropGradientsViewArray(INDArray) - Method in class org.deeplearning4j.nn.graph.vertex.impl.MergeVertex
-
- setBackpropGradientsViewArray(INDArray) - Method in class org.deeplearning4j.nn.graph.vertex.impl.PoolHelperVertex
-
- setBackpropGradientsViewArray(INDArray) - Method in class org.deeplearning4j.nn.graph.vertex.impl.PreprocessorVertex
-
- setBackpropGradientsViewArray(INDArray) - Method in class org.deeplearning4j.nn.graph.vertex.impl.ReshapeVertex
-
- setBackpropGradientsViewArray(INDArray) - Method in class org.deeplearning4j.nn.graph.vertex.impl.rnn.DuplicateToTimeSeriesVertex
-
- setBackpropGradientsViewArray(INDArray) - Method in class org.deeplearning4j.nn.graph.vertex.impl.rnn.LastTimeStepVertex
-
- setBackpropGradientsViewArray(INDArray) - Method in class org.deeplearning4j.nn.graph.vertex.impl.rnn.ReverseTimeSeriesVertex
-
- setBackpropGradientsViewArray(INDArray) - Method in class org.deeplearning4j.nn.graph.vertex.impl.ScaleVertex
-
- setBackpropGradientsViewArray(INDArray) - Method in class org.deeplearning4j.nn.graph.vertex.impl.ShiftVertex
-
- setBackpropGradientsViewArray(INDArray) - Method in class org.deeplearning4j.nn.graph.vertex.impl.StackVertex
-
- setBackpropGradientsViewArray(INDArray) - Method in class org.deeplearning4j.nn.graph.vertex.impl.SubsetVertex
-
- setBackpropGradientsViewArray(INDArray) - Method in class org.deeplearning4j.nn.graph.vertex.impl.UnstackVertex
-
- setBackpropGradientsViewArray(INDArray) - Method in class org.deeplearning4j.nn.layers.AbstractLayer
-
- setBackpropGradientsViewArray(INDArray) - Method in class org.deeplearning4j.nn.layers.BaseLayer
-
- setBackpropGradientsViewArray(INDArray) - Method in class org.deeplearning4j.nn.layers.FrozenLayer
-
- setBackpropGradientsViewArray(INDArray) - Method in class org.deeplearning4j.nn.layers.FrozenLayerWithBackprop
-
- setBackpropGradientsViewArray(INDArray) - Method in class org.deeplearning4j.nn.layers.recurrent.BidirectionalLayer
-
- setBackpropGradientsViewArray(INDArray) - Method in class org.deeplearning4j.nn.layers.samediff.SameDiffLayer
-
- setBackpropGradientsViewArray(INDArray) - Method in class org.deeplearning4j.nn.layers.variational.VariationalAutoencoder
-
- setBackpropGradientsViewArray(INDArray) - Method in class org.deeplearning4j.nn.layers.wrapper.BaseWrapperLayer
-
- setBackpropGradientsViewArray(INDArray) - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
-
- setBackpropGradientsViewArray(INDArray) - Method in class org.deeplearning4j.plot.BarnesHutTsne
-
- setBatchSize(int) - Method in interface org.deeplearning4j.optimize.api.ConvexOptimizer
-
Set the batch size for the optimizer
- setBatchSize(int) - Method in class org.deeplearning4j.optimize.solvers.BaseOptimizer
-
- setBegin(int) - Method in class org.deeplearning4j.nn.layers.feedforward.autoencoder.recursive.Tree
-
- setBegin(int) - Method in class org.deeplearning4j.text.movingwindow.Window
-
- setBias(INDArray) - Method in class org.deeplearning4j.models.glove.GloveWeightLookupTable
-
Deprecated.
- setBinCount(int) - Method in class org.deeplearning4j.ui.weights.HistogramBin.Builder
-
Specifies number of bins for output histogram
- setBoundary(Cell) - Method in class org.deeplearning4j.clustering.quadtree.QuadTree
-
- setBufferSizePerSplit(int) - Method in class org.deeplearning4j.datasets.iterator.parallel.JointParallelDataSetIterator.Builder
-
- setCacheMode(CacheMode) - Method in interface org.deeplearning4j.nn.api.Layer
-
This method sets given CacheMode for current layer
- setCacheMode(CacheMode) - Method in class org.deeplearning4j.nn.graph.ComputationGraph
-
This method sets specified CacheMode for all layers within network
- setCacheMode(CacheMode) - Method in class org.deeplearning4j.nn.layers.AbstractLayer
-
- setCacheMode(CacheMode) - Method in class org.deeplearning4j.nn.layers.FrozenLayer
-
- setCacheMode(CacheMode) - Method in class org.deeplearning4j.nn.layers.recurrent.BidirectionalLayer
-
- setCacheMode(CacheMode) - Method in class org.deeplearning4j.nn.layers.variational.VariationalAutoencoder
-
- setCacheMode(CacheMode) - Method in class org.deeplearning4j.nn.layers.wrapper.BaseWrapperLayer
-
- setCacheMode(CacheMode) - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
-
This method sets specified CacheMode for all layers within network
- setCachePerDevice(long) - Method in class org.deeplearning4j.models.word2vec.StaticWord2Vec.Builder
-
This method lets you to define if decompressed values will be cached, to avoid excessive decompressions.
- setCapacityPerFlow(int) - Method in class org.deeplearning4j.parallelism.MagicQueue.Builder
-
Deprecated.
This method defines, how
- setCasPool(CasPool) - Method in class org.deeplearning4j.text.uima.UimaResource
-
- setCategories(char, String[]) - Method in class com.atilika.kuromoji.dict.CharacterDefinitions
-
- setCenterOfMass(INDArray) - Method in class org.deeplearning4j.clustering.quadtree.QuadTree
-
- setChars(char[], int, int) - Method in interface org.ansj.splitWord.GetWords
-
- setChars(char[], int, int) - Method in class org.ansj.splitWord.impl.GetWordsImpl
-
- setClustersInfos(Map<String, ClusterInfo>) - Method in class org.deeplearning4j.clustering.info.ClusterSetInfo
-
- setCodeLength(short) - Method in class org.deeplearning4j.models.sequencevectors.sequence.SequenceElement
-
This method fills codes and points up to codeLength
- setCodes(Map<Integer, INDArray>) - Method in class org.deeplearning4j.models.embeddings.inmemory.InMemoryLookupTable
-
- setCodes(List<Byte>) - Method in class org.deeplearning4j.models.sequencevectors.sequence.SequenceElement
-
Sets Huffman tree codes
- setCollectMetaData(boolean) - Method in class org.deeplearning4j.datasets.datavec.RecordReaderDataSetIterator
-
When set to true: metadata for the current examples will be present in the returned DataSet.
- setCollectTrainingStats(boolean) - Method in interface org.deeplearning4j.spark.api.TrainingMaster
-
Set whether the training statistics should be collected.
- setCollectTrainingStats(boolean) - Method in class org.deeplearning4j.spark.impl.graph.SparkComputationGraph
-
- setCollectTrainingStats(boolean) - Method in class org.deeplearning4j.spark.impl.multilayer.SparkDl4jMultiLayer
-
Set whether training statistics should be collected for debugging purposes.
- setCollectTrainingStats(boolean) - Method in class org.deeplearning4j.spark.impl.paramavg.ParameterAveragingTrainingMaster
-
- setCollectTrainingStats(boolean) - Method in class org.deeplearning4j.spark.parameterserver.training.SharedTrainingMaster
-
- setConf(NeuralNetConfiguration) - Method in interface org.deeplearning4j.nn.api.Model
-
Setter for the configuration
- setConf(NeuralNetConfiguration) - Method in class org.deeplearning4j.nn.graph.ComputationGraph
-
- setConf(NeuralNetConfiguration) - Method in class org.deeplearning4j.nn.layers.AbstractLayer
-
- setConf(NeuralNetConfiguration) - Method in class org.deeplearning4j.nn.layers.recurrent.BidirectionalLayer
-
- setConf(NeuralNetConfiguration) - Method in class org.deeplearning4j.nn.layers.variational.VariationalAutoencoder
-
- setConf(NeuralNetConfiguration) - Method in class org.deeplearning4j.nn.layers.wrapper.BaseWrapperLayer
-
- setConf(NeuralNetConfiguration) - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
-
- setConf(NeuralNetConfiguration) - Method in class org.deeplearning4j.plot.BarnesHutTsne
-
- setConf(Configuration) - Method in class org.deeplearning4j.spark.datavec.iterator.SparkSourceDummyReader
-
- setConstraints(List<LayerConstraint>) - Method in class org.deeplearning4j.nn.conf.layers.misc.FrozenLayer
-
- setConstraints(List<LayerConstraint>) - Method in class org.deeplearning4j.nn.conf.layers.misc.FrozenLayerWithBackprop
-
- setContext(CamelContext) - Method in class org.deeplearning4j.streaming.routes.CamelKafkaRouteBuilder
-
- setCoOccurrenceCounts(Broadcast<CounterMap<String, String>>) - Method in class org.deeplearning4j.spark.models.embeddings.glove.GloveParam
-
- setCorner(int, double) - Method in class org.deeplearning4j.clustering.sptree.Cell
-
- setCorner(INDArray) - Method in class org.deeplearning4j.clustering.sptree.Cell
-
- setCount(AtomicInteger) - Method in class org.deeplearning4j.models.word2vec.StreamWork
-
- setCount(AtomicInteger) - Method in class org.deeplearning4j.models.word2vec.VocabWork
-
- setCounter(int) - Method in class org.deeplearning4j.parallelism.inference.observers.BatchedInferenceObservable
-
- setCountForDoc(String, long) - Method in class org.deeplearning4j.models.word2vec.wordstore.inmemory.AbstractCache
-
Set exact number of observed documents that contain specified word
Please note: this method is NOT thread-safe
- setCountForDoc(String, long) - Method in class org.deeplearning4j.models.word2vec.wordstore.inmemory.InMemoryLookupCache
-
Deprecated.
- setCountForDoc(String, long) - Method in interface org.deeplearning4j.models.word2vec.wordstore.VocabCache
-
Set the count for the number of documents the word appears in
- setCreds(AWSCredentials) - Method in class org.deeplearning4j.aws.s3.BaseS3
-
- setCrfModel(SplitWord) - Method in class org.ansj.splitWord.analysis.NlpAnalysis
-
- setCumSize(int) - Method in class org.deeplearning4j.clustering.quadtree.QuadTree
-
- setCumSize(int) - Method in class org.deeplearning4j.clustering.sptree.SpTree
-
- setCurrent(int) - Method in class org.deeplearning4j.datasets.mnist.MnistManager
-
Set the position to be read.
- setCurrentIndex(long) - Method in class org.deeplearning4j.datasets.mnist.MnistDbFile
-
Set the required current entry index.
- setData(INDArray) - Method in class org.deeplearning4j.plot.BarnesHutTsne
-
- setDefaultCollapsed(boolean) - Method in class org.deeplearning4j.ui.components.decorator.DecoratorAccordion.Builder
-
Set the default collapsed/expanded state
- setDefaultLanguage(String) - Method in interface org.deeplearning4j.ui.api.I18N
-
Set the default language
- setDefaultLanguage(String) - Method in class org.deeplearning4j.ui.i18n.DefaultI18N
-
- setDepth(int) - Method in class org.deeplearning4j.models.sequencevectors.graph.walkers.impl.NearestVertexWalker.Builder
-
This method specifies, how deep walker goes from starting point
Default value: 1
- setDepth(int) - Method in class org.deeplearning4j.nn.conf.inputs.InputType.InputTypeConvolutional
-
Deprecated.
- setDictionaryEntries(List<GenericDictionaryEntry>) - Method in class com.atilika.kuromoji.compile.TokenInfoDictionaryCompilerBase
-
Deprecated.
- setDistance(double) - Method in class org.deeplearning4j.clustering.sptree.HeapItem
-
- setDistancesBetweenClustersCenters(Table<String, String, Double>) - Method in class org.deeplearning4j.clustering.info.ClusterSetInfo
-
- setElementFrequency(long) - Method in class org.deeplearning4j.models.sequencevectors.sequence.SequenceElement
-
This method sets frequency value for this element
- setElementsLearningAlgorithm(SparkElementsLearningAlgorithm) - Method in class org.deeplearning4j.spark.models.sequencevectors.SparkSequenceVectors.Builder
-
- setElementsLearningAlgorithm(SparkElementsLearningAlgorithm) - Method in class org.deeplearning4j.spark.models.word2vec.SparkWord2Vec.Builder
-
- setEnabled(boolean) - Method in class org.deeplearning4j.ui.module.remote.RemoteReceiverModule
-
- setEnd(int) - Method in class org.deeplearning4j.nn.layers.feedforward.autoencoder.recursive.Tree
-
- setEnd(int) - Method in class org.deeplearning4j.text.movingwindow.Window
-
- setEntriesLimit(int) - Method in class org.deeplearning4j.models.word2vec.wordstore.VocabConstructor.Builder
-
This method sets the limit to resulting vocabulary size.
- setEpochCount(int) - Method in interface org.deeplearning4j.nn.api.Layer
-
Set the current epoch count (number of epochs passed ) for the layer/network
- setEpochCount(int) - Method in class org.deeplearning4j.nn.layers.recurrent.BidirectionalLayer
-
- setEpochCount(int) - Method in class org.deeplearning4j.nn.layers.wrapper.BaseWrapperLayer
-
- setEpochCount(int) - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
-
- setEpsilon(INDArray) - Method in class org.deeplearning4j.nn.graph.vertex.BaseGraphVertex
-
- setEpsilon(INDArray) - Method in class org.deeplearning4j.nn.graph.vertex.BaseWrapperVertex
-
- setEpsilon(INDArray) - Method in interface org.deeplearning4j.nn.graph.vertex.GraphVertex
-
Set the errors (epsilon - aka dL/dActivation) for this GraphVertex
- setError(double) - Method in class org.deeplearning4j.nn.layers.feedforward.autoencoder.recursive.Tree
-
- setError(double) - Method in class org.deeplearning4j.spark.models.embeddings.glove.GloveChange
-
- setExpTable(double[]) - Method in class org.deeplearning4j.models.embeddings.inmemory.InMemoryLookupTable
-
- setExpTable(Broadcast<double[]>) - Method in class org.deeplearning4j.spark.models.embeddings.word2vec.Word2VecParam
-
Deprecated.
- setExpTable(double[]) - Method in class org.deeplearning4j.spark.models.embeddings.word2vec.Word2VecPerformerVoid
-
Deprecated.
- setExternalSource(Queue<INDArray>) - Method in class org.deeplearning4j.optimize.solvers.accumulation.BasicGradientsAccumulator
-
- setExternalSource(Queue<INDArray>) - Method in class org.deeplearning4j.optimize.solvers.accumulation.EncodedGradientsAccumulator
-
This method allows to pass external updates to accumulator, they will be populated across all workers using this GradientsAccumulator instance
- setExternalSource(Queue<INDArray>) - Method in interface org.deeplearning4j.optimize.solvers.accumulation.GradientsAccumulator
-
This method allows to pass external updates to accumulator, they will be populated across all workers using this GradientsAccumulator instance
- setFeatureExtractor(int) - Method in class org.deeplearning4j.nn.transferlearning.TransferLearning.Builder
-
Specify a layer to set as a "feature extractor"
The specified layer and the layers preceding it will be "frozen" with parameters staying constant
- setFeatureExtractor(String...) - Method in class org.deeplearning4j.nn.transferlearning.TransferLearning.GraphBuilder
-
Specify a layer vertex to set as a "feature extractor"
The specified layer vertex and the layers on the path from an input vertex to it it will be "frozen" with parameters staying constant
- setFetchSize(int) - Method in class org.deeplearning4j.text.sentenceiterator.PrefetchingSentenceIterator.Builder
-
Deprecated.
- setFetchSize(int) - Method in class org.deeplearning4j.text.sentenceiterator.StreamLineIterator.Builder
-
- setFilenamePrefix(boolean) - Method in class org.deeplearning4j.models.sequencevectors.listeners.SerializingListener.Builder
-
This method allows you to define template for file names that will be created during serialization
- setFinalMomentum(double) - Method in class org.deeplearning4j.plot.BarnesHutTsne.Builder
-
- setFinalMomentum(double) - Method in class org.deeplearning4j.plot.Tsne.Builder
-
- setForests(Forest...) - Method in class org.ansj.splitWord.Analysis
-
- setFrameId(long) - Method in class org.deeplearning4j.spark.parameterserver.networking.messages.SilentUpdatesMessage
-
- setFrequency(int) - Method in class org.deeplearning4j.optimize.listeners.PerformanceListener.Builder
-
Desired TrainingListener activation frequency
- setFrom(Term) - Method in class org.ansj.domain.Term
-
- setGain(double) - Method in class org.deeplearning4j.nn.conf.distribution.OrthogonalDistribution
-
- setGen(Random) - Method in class org.deeplearning4j.spark.models.embeddings.glove.GloveParam
-
- setGoldLabel(int) - Method in class org.deeplearning4j.nn.layers.feedforward.autoencoder.recursive.Tree
-
- setGradientFor(String, INDArray) - Method in class org.deeplearning4j.nn.gradient.DefaultGradient
-
- setGradientFor(String, INDArray, Character) - Method in class org.deeplearning4j.nn.gradient.DefaultGradient
-
- setGradientFor(String, INDArray) - Method in interface org.deeplearning4j.nn.gradient.Gradient
-
Update gradient for the given variable
- setGradientFor(String, INDArray, Character) - Method in interface org.deeplearning4j.nn.gradient.Gradient
-
Update gradient for the given variable; also (optionally) specify the order in which the array should be flattened
to a row vector
- setGradients(Map<String, Map>) - Method in class org.deeplearning4j.ui.weights.beans.CompactModelAndGradient
-
- setGradientsAccumulator(GradientsAccumulator) - Method in class org.deeplearning4j.nn.graph.ComputationGraph
-
This method allows you to specificy GradientsAccumulator instance to be used with this model
- setGradientsAccumulator(GradientsAccumulator) - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
-
This method allows you to specificy GradientsAccumulator instance to be used with this model
PLEASE NOTE: Do not use this method unless you understand how to use GradientsAccumulator & updates sharing.
- setGradientsAccumulator(GradientsAccumulator) - Method in interface org.deeplearning4j.optimize.api.ConvexOptimizer
-
This method specifies GradientsAccumulator instance to be used for updates sharing across multiple models
- setGradientsAccumulator(GradientsAccumulator) - Method in class org.deeplearning4j.optimize.solvers.BaseOptimizer
-
- setGraphWalker(GraphWalker<T>) - Method in class org.deeplearning4j.models.sequencevectors.transformers.impl.GraphTransformer.Builder
-
- setGridWidth(Double, Double) - Method in class org.deeplearning4j.ui.components.chart.Chart.Builder
-
Set the grid lines to be enabled, and if enabled: set the grid.
- setGridWidth(Integer, Integer) - Method in class org.deeplearning4j.ui.components.chart.Chart.Builder
-
Set the grid lines to be enabled, and if enabled: set the grid.
- setHeadWord(String) - Method in class org.deeplearning4j.nn.layers.feedforward.autoencoder.recursive.Tree
-
- setHh(double) - Method in class org.deeplearning4j.clustering.quadtree.Cell
-
- setHistoricalGradient(INDArray) - Method in class org.deeplearning4j.models.sequencevectors.sequence.SequenceElement
-
Deprecated.
- setHw(double) - Method in class org.deeplearning4j.clustering.quadtree.Cell
-
- setInboundLayerNames(List<String>) - Method in class org.deeplearning4j.nn.modelimport.keras.KerasLayer
-
Set list of inbound layers.
- setIndex(int) - Method in class org.deeplearning4j.clustering.sptree.HeapItem
-
- setIndex(int) - Method in class org.deeplearning4j.models.sequencevectors.sequence.SequenceElement
-
Sets index in Huffman tree
- setIndex(InvertedIndex<T>) - Method in class org.deeplearning4j.models.word2vec.wordstore.VocabConstructor.Builder
-
- setIndex(int) - Method in interface org.deeplearning4j.nn.api.Layer
-
Set the layer index.
- setIndex(int) - Method in class org.deeplearning4j.nn.layers.AbstractLayer
-
- setIndex(int) - Method in class org.deeplearning4j.nn.layers.normalization.BatchNormalization
-
- setIndex(int) - Method in class org.deeplearning4j.nn.layers.recurrent.BidirectionalLayer
-
- setIndex(int) - Method in class org.deeplearning4j.nn.layers.variational.VariationalAutoencoder
-
- setIndex(int) - Method in class org.deeplearning4j.nn.layers.wrapper.BaseWrapperLayer
-
- setIndex(int) - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
-
- setInitialMomentum(double) - Method in class org.deeplearning4j.plot.BarnesHutTsne.Builder
-
- setInitialMomentum(double) - Method in class org.deeplearning4j.plot.Tsne.Builder
-
- setInput(INDArray, LayerWorkspaceMgr) - Method in interface org.deeplearning4j.nn.api.Layer
-
Set the layer input.
- setInput(int, INDArray) - Method in class org.deeplearning4j.nn.graph.ComputationGraph
-
Set the specified input for the ComputationGraph
- setInput(int, INDArray, LayerWorkspaceMgr) - Method in class org.deeplearning4j.nn.graph.vertex.BaseGraphVertex
-
- setInput(int, INDArray, LayerWorkspaceMgr) - Method in class org.deeplearning4j.nn.graph.vertex.BaseWrapperVertex
-
- setInput(int, INDArray, LayerWorkspaceMgr) - Method in interface org.deeplearning4j.nn.graph.vertex.GraphVertex
-
Set the input activations.
- setInput(int, INDArray, LayerWorkspaceMgr) - Method in class org.deeplearning4j.nn.graph.vertex.impl.LayerVertex
-
- setInput(INDArray, LayerWorkspaceMgr) - Method in class org.deeplearning4j.nn.layers.AbstractLayer
-
- setInput(INDArray, LayerWorkspaceMgr) - Method in class org.deeplearning4j.nn.layers.recurrent.BidirectionalLayer
-
- setInput(INDArray, LayerWorkspaceMgr) - Method in class org.deeplearning4j.nn.layers.variational.VariationalAutoencoder
-
- setInput(INDArray, LayerWorkspaceMgr) - Method in class org.deeplearning4j.nn.layers.wrapper.BaseWrapperLayer
-
- setInput(INDArray) - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
-
Note that if input isn't null
and the neuralNets are null, this is a way
of initializing the neural network
- setInput(INDArray, LayerWorkspaceMgr) - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
-
- setInput(Observer, INDArray) - Method in class org.deeplearning4j.parallelism.ParallelInference.ObservablesProvider
-
- setInput(Observer, INDArray...) - Method in class org.deeplearning4j.parallelism.ParallelInference.ObservablesProvider
-
- setInput(Observer, INDArray[], INDArray[]) - Method in class org.deeplearning4j.parallelism.ParallelInference.ObservablesProvider
-
- setInputMiniBatchSize(int) - Method in interface org.deeplearning4j.nn.api.Layer
-
Set current/last input mini-batch size.
Used for score and gradient calculations.
- setInputMiniBatchSize(int) - Method in class org.deeplearning4j.nn.layers.AbstractLayer
-
- setInputMiniBatchSize(int) - Method in class org.deeplearning4j.nn.layers.recurrent.BidirectionalLayer
-
- setInputMiniBatchSize(int) - Method in class org.deeplearning4j.nn.layers.variational.VariationalAutoencoder
-
- setInputMiniBatchSize(int) - Method in class org.deeplearning4j.nn.layers.wrapper.BaseWrapperLayer
-
- setInputMiniBatchSize(int) - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
-
- setInputPreProcessor(int, InputPreProcessor) - Method in class org.deeplearning4j.nn.transferlearning.TransferLearning.Builder
-
Specify the preprocessor for the added layers
for cases where they cannot be inferred automatically.
- setInputs(INDArray...) - Method in class org.deeplearning4j.nn.graph.ComputationGraph
-
Set all inputs for the ComputationGraph network
- setInputs(INDArray...) - Method in class org.deeplearning4j.nn.graph.vertex.BaseWrapperVertex
-
- setInputs(INDArray...) - Method in interface org.deeplearning4j.nn.graph.vertex.GraphVertex
-
Set all inputs for this GraphVertex
- setInputs(String...) - Method in class org.deeplearning4j.nn.transferlearning.TransferLearning.GraphBuilder
-
Sets new inputs for the computation graph.
- setInputShape(int[][]) - Method in interface org.deeplearning4j.zoo.InstantiableModel
-
- setInputShape(int[][]) - Method in class org.deeplearning4j.zoo.model.AlexNet
-
- setInputShape(int[][]) - Method in class org.deeplearning4j.zoo.model.Darknet19
-
- setInputShape(int[][]) - Method in class org.deeplearning4j.zoo.model.FaceNetNN4Small2
-
- setInputShape(int[][]) - Method in class org.deeplearning4j.zoo.model.InceptionResNetV1
-
- setInputShape(int[][]) - Method in class org.deeplearning4j.zoo.model.LeNet
-
- setInputShape(int[][]) - Method in class org.deeplearning4j.zoo.model.NASNet
-
- setInputShape(int[][]) - Method in class org.deeplearning4j.zoo.model.ResNet50
-
- setInputShape(int[][]) - Method in class org.deeplearning4j.zoo.model.SimpleCNN
-
- setInputShape(int[][]) - Method in class org.deeplearning4j.zoo.model.SqueezeNet
-
- setInputShape(int[][]) - Method in class org.deeplearning4j.zoo.model.TextGenerationLSTM
-
- setInputShape(int[][]) - Method in class org.deeplearning4j.zoo.model.TinyYOLO
-
- setInputShape(int[][]) - Method in class org.deeplearning4j.zoo.model.UNet
-
- setInputShape(int[][]) - Method in class org.deeplearning4j.zoo.model.VGG16
-
- setInputShape(int[][]) - Method in class org.deeplearning4j.zoo.model.VGG19
-
- setInputShape(int[][]) - Method in class org.deeplearning4j.zoo.model.Xception
-
- setInputShape(int[][]) - Method in class org.deeplearning4j.zoo.model.YOLO2
-
- setInputType(InputType) - Method in class org.deeplearning4j.nn.conf.MultiLayerConfiguration.Builder
-
- setInputType(InputType) - Method in class org.deeplearning4j.nn.conf.NeuralNetConfiguration.ListBuilder
-
- setInputTypes(InputType...) - Method in class org.deeplearning4j.nn.conf.ComputationGraphConfiguration.GraphBuilder
-
Specify the types of inputs to the network, so that:
(a) preprocessors can be automatically added, and
(b) the nIns (input size) for each layer can be automatically calculated and set
The order here is the same order as .addInputs().
- setInputTypes(InputType...) - Method in class org.deeplearning4j.nn.transferlearning.TransferLearning.GraphBuilder
-
Sets the input type of corresponding inputs.
- setInputVertices(VertexIndices[]) - Method in class org.deeplearning4j.nn.graph.vertex.BaseGraphVertex
-
- setInputVertices(VertexIndices[]) - Method in class org.deeplearning4j.nn.graph.vertex.BaseWrapperVertex
-
- setInputVertices(VertexIndices[]) - Method in interface org.deeplearning4j.nn.graph.vertex.GraphVertex
-
Sets the input vertices.
- setInvert(boolean) - Method in class org.deeplearning4j.plot.BarnesHutTsne
-
- setIsNameRecognition(Boolean) - Method in class org.ansj.splitWord.Analysis
-
- setIsNumRecognition(Boolean) - Method in class org.ansj.splitWord.Analysis
-
- setIsQuantifierRecognition(Boolean) - Method in class org.ansj.splitWord.Analysis
-
- setIsRealName(Boolean) - Method in class org.ansj.splitWord.Analysis
-
- setIterationCount(int) - Method in interface org.deeplearning4j.nn.api.Layer
-
Set the current iteration count (number of parameter updates) for the layer/network
- setIterationCount(int) - Method in class org.deeplearning4j.nn.layers.recurrent.BidirectionalLayer
-
- setIterationCount(int) - Method in class org.deeplearning4j.nn.layers.wrapper.BaseWrapperLayer
-
- setIterationCount(int) - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
-
- setIterations(int) - Method in class org.deeplearning4j.spark.models.embeddings.word2vec.Word2VecPerformerVoid
-
Deprecated.
- setIterator(LabelAwareIterator) - Method in class org.deeplearning4j.bagofwords.vectorizer.BagOfWordsVectorizer.Builder
-
- setIterator(DocumentIterator) - Method in class org.deeplearning4j.bagofwords.vectorizer.BagOfWordsVectorizer.Builder
-
- setIterator(SentenceIterator) - Method in class org.deeplearning4j.bagofwords.vectorizer.BagOfWordsVectorizer.Builder
-
- setIterator(LabelAwareIterator) - Method in class org.deeplearning4j.bagofwords.vectorizer.TfidfVectorizer.Builder
-
- setIterator(DocumentIterator) - Method in class org.deeplearning4j.bagofwords.vectorizer.TfidfVectorizer.Builder
-
- setIterator(SentenceIterator) - Method in class org.deeplearning4j.bagofwords.vectorizer.TfidfVectorizer.Builder
-
- setIWM - Variable in class org.deeplearning4j.nn.conf.NeuralNetConfiguration.Builder
-
- setK(K) - Method in class org.ansj.domain.KV
-
- setLabel(List<String>) - Method in class org.deeplearning4j.models.word2vec.VocabWork
-
- setLabel(int, INDArray) - Method in class org.deeplearning4j.nn.graph.ComputationGraph
-
Set the specified label for the ComputationGraph
- setLabel(String) - Method in class org.deeplearning4j.nn.layers.feedforward.autoencoder.recursive.Tree
-
- setLabel(String) - Method in class org.deeplearning4j.text.documentiterator.LabelledDocument
-
Deprecated.
- setLabel(String) - Method in class org.deeplearning4j.text.movingwindow.Window
-
- setLabelNames(List<String>) - Method in class org.deeplearning4j.eval.EvaluationBinary
-
- setLabelNames(List<String>) - Method in class org.deeplearning4j.eval.ROCBinary
-
- setLabels(INDArray) - Method in interface org.deeplearning4j.nn.api.layers.IOutputLayer
-
Set the labels array for this output layer
- setLabels(INDArray...) - Method in class org.deeplearning4j.nn.graph.ComputationGraph
-
Set all labels for the ComputationGraph network
- setLabels(INDArray) - Method in class org.deeplearning4j.nn.layers.BaseOutputLayer
-
- setLabels(INDArray) - Method in class org.deeplearning4j.nn.layers.LossLayer
-
- setLabels(INDArray) - Method in class org.deeplearning4j.nn.layers.ocnn.OCNNOutputLayer
-
- setLabels(INDArray) - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
-
- setLabelsProvider(LabelsProvider<T>) - Method in class org.deeplearning4j.models.sequencevectors.transformers.impl.GraphTransformer.Builder
-
- setLabelsSource(LabelsSource) - Method in class org.deeplearning4j.text.documentiterator.BasicLabelAwareIterator.Builder
-
TODO: To be implemented
- setLabelTemplate(String) - Method in class org.deeplearning4j.text.documentiterator.BasicLabelAwareIterator.Builder
-
Label template will be used for sentence labels generation.
- setLastChecked(int) - Method in class org.deeplearning4j.spark.models.embeddings.word2vec.Word2VecParam
-
Deprecated.
- setLastChecked(int) - Method in class org.deeplearning4j.spark.models.embeddings.word2vec.Word2VecPerformerVoid
-
Deprecated.
- setLastEtlTime(long) - Method in class org.deeplearning4j.nn.graph.ComputationGraph
-
This method allows to set ETL field time, useful for performance tracking
- setLastEtlTime(long) - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
-
- setLastUpdateTime(long) - Method in class org.deeplearning4j.ui.weights.beans.CompactModelAndGradient
-
- setLastWords(AtomicLong) - Method in class org.deeplearning4j.spark.models.embeddings.word2vec.Word2VecParam
-
Deprecated.
- setLatestScore(double) - Method in class org.deeplearning4j.parallelism.EarlyStoppingParallelTrainer
-
- setLayerAsFrozen() - Method in class org.deeplearning4j.nn.graph.vertex.BaseGraphVertex
-
- setLayerAsFrozen() - Method in class org.deeplearning4j.nn.graph.vertex.BaseWrapperVertex
-
- setLayerAsFrozen() - Method in interface org.deeplearning4j.nn.graph.vertex.GraphVertex
-
Only applies to layer vertices.
- setLayerAsFrozen() - Method in class org.deeplearning4j.nn.graph.vertex.impl.LayerVertex
-
- setLayerMaskArrays(INDArray[], INDArray[]) - Method in class org.deeplearning4j.nn.graph.ComputationGraph
-
Set the mask arrays for features and labels.
- setLayerMaskArrays(INDArray, INDArray) - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
-
Set the mask arrays for features and labels.
- setLayerName(String) - Method in class org.deeplearning4j.nn.conf.layers.misc.FrozenLayer
-
- setLayerName(String) - Method in class org.deeplearning4j.nn.conf.layers.misc.FrozenLayerWithBackprop
-
- setLayerName(String) - Method in class org.deeplearning4j.nn.conf.layers.recurrent.Bidirectional
-
- setLayerNames(List<String>) - Method in class org.deeplearning4j.ui.weights.beans.CompactModelAndGradient
-
- setLayerParamLR(String) - Method in class org.deeplearning4j.nn.conf.NeuralNetConfiguration
-
- setLayers(Layer[]) - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
-
- setLayerWiseConfigurations(MultiLayerConfiguration) - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
-
- setLeaf(boolean) - Method in class org.deeplearning4j.clustering.quadtree.QuadTree
-
- setLearningAlgorithm(SparkElementsLearningAlgorithm) - Method in class org.deeplearning4j.spark.models.word2vec.SparkWord2Vec.Builder
-
This method defines the learning algorithm that will be used during training
- setLearningRate(double) - Method in class org.deeplearning4j.graph.models.deepwalk.DeepWalk
-
- setLearningRate(double) - Method in interface org.deeplearning4j.graph.models.embeddings.GraphVectorLookupTable
-
Set the learning rate
- setLearningRate(double) - Method in class org.deeplearning4j.graph.models.embeddings.InMemoryGraphLookupTable
-
- setLearningRate(double) - Method in class org.deeplearning4j.models.embeddings.inmemory.InMemoryLookupTable
-
- setLearningRate(double) - Method in interface org.deeplearning4j.models.embeddings.WeightLookupTable
-
Sets the learning rate
- setLearningRate(double) - Method in class org.deeplearning4j.nn.graph.ComputationGraph
-
Set the learning rate for all layers in the network to the specified value.
- setLearningRate(ISchedule) - Method in class org.deeplearning4j.nn.graph.ComputationGraph
-
Set the learning rate schedule for all layers in the network to the specified schedule.
- setLearningRate(String, double) - Method in class org.deeplearning4j.nn.graph.ComputationGraph
-
Set the learning rate for a single layer in the network to the specified value.
- setLearningRate(String, ISchedule) - Method in class org.deeplearning4j.nn.graph.ComputationGraph
-
Set the learning rate schedule for a single layer in the network to the specified value.
Note also that
ComputationGraph.setLearningRate(ISchedule) should also be used in preference, when all layers need
to be set to a new LR schedule.
This schedule will replace any/all existing schedules, and also any fixed learning rate values.
Note also that the iteration/epoch counts will
not be reset.
- setLearningRate(double) - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
-
Set the learning rate for all layers in the network to the specified value.
- setLearningRate(ISchedule) - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
-
Set the learning rate schedule for all layers in the network to the specified schedule.
- setLearningRate(int, double) - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
-
Set the learning rate for a single layer in the network to the specified value.
- setLearningRate(int, ISchedule) - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
-
Set the learning rate schedule for a single layer in the network to the specified value.
Note also that
MultiLayerNetwork.setLearningRate(ISchedule) should also be used in preference, when all layers need
to be set to a new LR schedule.
This schedule will replace any/all existing schedules, and also any fixed learning rate values.
Note also that the iteration/epoch counts will
not be reset.
- setLearningRate(double) - Method in class org.deeplearning4j.spark.models.sequencevectors.SparkSequenceVectors.Builder
-
- setLearningRate(double) - Method in class org.deeplearning4j.spark.models.word2vec.SparkWord2Vec.Builder
-
- setLearningRate(MultiLayerNetwork, double) - Static method in class org.deeplearning4j.util.NetworkUtils
-
Set the learning rate for all layers in the network to the specified value.
- setLearningRate(MultiLayerNetwork, ISchedule) - Static method in class org.deeplearning4j.util.NetworkUtils
-
Set the learning rate schedule for all layers in the network to the specified schedule.
- setLearningRate(MultiLayerNetwork, int, double) - Static method in class org.deeplearning4j.util.NetworkUtils
-
Set the learning rate for a single layer in the network to the specified value.
- setLearningRate(MultiLayerNetwork, int, ISchedule) - Static method in class org.deeplearning4j.util.NetworkUtils
-
Set the learning rate schedule for a single layer in the network to the specified value.
Note also that
NetworkUtils.setLearningRate(MultiLayerNetwork, ISchedule) should also be used in preference, when all layers need
to be set to a new LR schedule.
This schedule will replace any/all existing schedules, and also any fixed learning rate values.
Note also that the iteration/epoch counts will
not be reset.
- setLearningRate(ComputationGraph, double) - Static method in class org.deeplearning4j.util.NetworkUtils
-
Set the learning rate for all layers in the network to the specified value.
- setLearningRate(ComputationGraph, ISchedule) - Static method in class org.deeplearning4j.util.NetworkUtils
-
Set the learning rate schedule for all layers in the network to the specified schedule.
- setLearningRate(ComputationGraph, String, double) - Static method in class org.deeplearning4j.util.NetworkUtils
-
Set the learning rate for a single layer in the network to the specified value.
- setLearningRate(ComputationGraph, String, ISchedule) - Static method in class org.deeplearning4j.util.NetworkUtils
-
Set the learning rate schedule for a single layer in the network to the specified value.
Note also that
NetworkUtils.setLearningRate(ComputationGraph, ISchedule) should also be used in preference, when all
layers need to be set to a new LR schedule.
This schedule will replace any/all existing schedules, and also any fixed learning rate values.
Note also that the iteration/epoch counts will
not be reset.
- setLearnTool(LearnTool) - Method in class org.ansj.splitWord.analysis.NlpAnalysis
-
- setLeft(PatriciaTrie.PatriciaNode<V>) - Method in class com.atilika.kuromoji.trie.PatriciaTrie.PatriciaNode
-
Set this node's left node
- setLeft(KDTree.KDNode) - Method in class org.deeplearning4j.clustering.kdtree.KDTree.KDNode
-
- setLeftNode(ViterbiNode) - Method in class com.atilika.kuromoji.viterbi.ViterbiNode
-
- setListener(EarlyStoppingListener<T>) - Method in class org.deeplearning4j.earlystopping.trainer.BaseEarlyStoppingTrainer
-
- setListener(EarlyStoppingListener<T>) - Method in interface org.deeplearning4j.earlystopping.trainer.IEarlyStoppingTrainer
-
Set the early stopping listener
- setListener(EarlyStoppingListener<T>) - Method in class org.deeplearning4j.parallelism.EarlyStoppingParallelTrainer
-
- setListener(EarlyStoppingListener<T>) - Method in class org.deeplearning4j.spark.earlystopping.BaseSparkEarlyStoppingTrainer
-
- setListeners(TrainingListener...) - Method in interface org.deeplearning4j.nn.api.Layer
-
Set the iteration listeners for this layer.
- setListeners(Collection<TrainingListener>) - Method in interface org.deeplearning4j.nn.api.Layer
-
Set the iteration listeners for this layer.
- setListeners(Collection<TrainingListener>) - Method in interface org.deeplearning4j.nn.api.Model
-
Set the trainingListeners for the ComputationGraph (and all layers in the network)
- setListeners(TrainingListener...) - Method in interface org.deeplearning4j.nn.api.Model
-
Set the trainingListeners for the ComputationGraph (and all layers in the network)
- setListeners(Collection<TrainingListener>) - Method in class org.deeplearning4j.nn.graph.ComputationGraph
-
Set the trainingListeners for the ComputationGraph (and all layers in the network)
- setListeners(TrainingListener...) - Method in class org.deeplearning4j.nn.graph.ComputationGraph
-
Set the trainingListeners for the ComputationGraph (and all layers in the network)
- setListeners(Collection<TrainingListener>) - Method in class org.deeplearning4j.nn.layers.AbstractLayer
-
- setListeners(TrainingListener...) - Method in class org.deeplearning4j.nn.layers.AbstractLayer
-
- setListeners(TrainingListener...) - Method in class org.deeplearning4j.nn.layers.normalization.BatchNormalization
-
- setListeners(TrainingListener...) - Method in class org.deeplearning4j.nn.layers.recurrent.BidirectionalLayer
-
- setListeners(Collection<TrainingListener>) - Method in class org.deeplearning4j.nn.layers.recurrent.BidirectionalLayer
-
- setListeners(TrainingListener...) - Method in class org.deeplearning4j.nn.layers.variational.VariationalAutoencoder
-
- setListeners(Collection<TrainingListener>) - Method in class org.deeplearning4j.nn.layers.variational.VariationalAutoencoder
-
- setListeners(TrainingListener...) - Method in class org.deeplearning4j.nn.layers.wrapper.BaseWrapperLayer
-
- setListeners(Collection<TrainingListener>) - Method in class org.deeplearning4j.nn.layers.wrapper.BaseWrapperLayer
-
- setListeners(Collection<TrainingListener>) - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
-
- setListeners(TrainingListener...) - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
-
- setListeners(Collection<TrainingListener>) - Method in interface org.deeplearning4j.optimize.api.ConvexOptimizer
-
- setListeners(Collection<TrainingListener>) - Method in class org.deeplearning4j.optimize.Solver
-
- setListeners(Collection<TrainingListener>) - Method in class org.deeplearning4j.optimize.solvers.BaseOptimizer
-
- setListeners(Collection<TrainingListener>) - Method in class org.deeplearning4j.parallelism.ParallelWrapper
-
This method allows you to specify trainingListeners for this model.
- setListeners(TrainingListener...) - Method in class org.deeplearning4j.parallelism.ParallelWrapper
-
This method allows you to specify trainingListeners for this model.
- setListeners(StatsStorageRouter, TrainingListener...) - Method in class org.deeplearning4j.parallelism.ParallelWrapper
-
Set the listeners, along with a StatsStorageRouter that the results will be shuffled to (in the case of any listeners
that implement the
RoutingIterationListener interface)
- setListeners(StatsStorageRouter, Collection<? extends TrainingListener>) - Method in class org.deeplearning4j.parallelism.ParallelWrapper
-
Set the listeners, along with a StatsStorageRouter that the results will be shuffled to (in the case of any listeners
that implement the
RoutingIterationListener interface)
- setListeners(Collection<TrainingListener>) - Method in class org.deeplearning4j.plot.BarnesHutTsne
-
Set the trainingListeners for the ComputationGraph (and all layers in the network)
- setListeners(TrainingListener...) - Method in class org.deeplearning4j.plot.BarnesHutTsne
-
Set the trainingListeners for the ComputationGraph (and all layers in the network)
- setListeners(Collection<TrainingListener>) - Method in interface org.deeplearning4j.spark.api.TrainingMaster
-
Set the iteration listeners.
- setListeners(StatsStorageRouter, Collection<TrainingListener>) - Method in interface org.deeplearning4j.spark.api.TrainingMaster
-
Set the iteration listeners and the StatsStorageRouter.
- setListeners(RecordListener...) - Method in class org.deeplearning4j.spark.datavec.iterator.SparkSourceDummyReader
-
- setListeners(Collection<RecordListener>) - Method in class org.deeplearning4j.spark.datavec.iterator.SparkSourceDummyReader
-
- setListeners(Collection<TrainingListener>) - Method in class org.deeplearning4j.spark.impl.paramavg.ParameterAveragingTrainingMaster
-
- setListeners(StatsStorageRouter, Collection<TrainingListener>) - Method in class org.deeplearning4j.spark.impl.paramavg.ParameterAveragingTrainingMaster
-
- setListeners(Collection<TrainingListener>) - Method in class org.deeplearning4j.spark.impl.SparkListenable
-
This method allows you to specify trainingListeners for this model.
- setListeners(TrainingListener...) - Method in class org.deeplearning4j.spark.impl.SparkListenable
-
This method allows you to specify trainingListeners for this model.
- setListeners(StatsStorageRouter, TrainingListener...) - Method in class org.deeplearning4j.spark.impl.SparkListenable
-
Set the listeners, along with a StatsStorageRouter that the results will be shuffled to (in the
case of any listeners that implement the
RoutingIterationListener interface)
- setListeners(StatsStorageRouter, Collection<? extends TrainingListener>) - Method in class org.deeplearning4j.spark.impl.SparkListenable
-
Set the listeners, along with a StatsStorageRouter that the results will be shuffled to (in the
case of any listeners that implement the
RoutingIterationListener interface)
- setListeners(Collection<TrainingListener>) - Method in class org.deeplearning4j.spark.parameterserver.training.SharedTrainingMaster
-
- setListeners(StatsStorageRouter, Collection<TrainingListener>) - Method in class org.deeplearning4j.spark.parameterserver.training.SharedTrainingMaster
-
- setlocFreq(int[][]) - Method in class org.ansj.domain.PersonNatureAttr
-
词频记录表
- setLogin(String) - Method in class org.deeplearning4j.ui.UiConnectionInfo.Builder
-
- setLookupTable(WeightLookupTable) - Method in class org.deeplearning4j.models.embeddings.wordvectors.WordVectorsImpl
-
- setLower(double) - Method in class org.deeplearning4j.nn.conf.distribution.UniformDistribution
-
- setLr(AtomicDouble) - Method in class org.deeplearning4j.models.embeddings.inmemory.InMemoryLookupTable
-
- setLr(double) - Method in class org.deeplearning4j.spark.models.embeddings.glove.GloveParam
-
- setMask(INDArray) - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
-
- setMaskArray(INDArray) - Method in interface org.deeplearning4j.nn.api.Layer
-
Set the mask array.
- setMaskArray(INDArray) - Method in class org.deeplearning4j.nn.layers.AbstractLayer
-
- setMaskArray(INDArray) - Method in class org.deeplearning4j.nn.layers.convolution.CnnLossLayer
-
- setMaskArray(INDArray) - Method in class org.deeplearning4j.nn.layers.recurrent.BidirectionalLayer
-
- setMaskArray(INDArray) - Method in class org.deeplearning4j.nn.layers.recurrent.RnnLossLayer
-
- setMaskArray(INDArray) - Method in class org.deeplearning4j.nn.layers.recurrent.RnnOutputLayer
-
- setMaskArray(INDArray) - Method in class org.deeplearning4j.nn.layers.variational.VariationalAutoencoder
-
- setMaskArray(INDArray) - Method in class org.deeplearning4j.nn.layers.wrapper.BaseWrapperLayer
-
- setMaskArray(INDArray) - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
-
- setMAX_EXP(double) - Static method in class org.deeplearning4j.spark.models.embeddings.word2vec.Word2VecPerformerVoid
-
Deprecated.
- setMaxCount(double) - Method in class org.deeplearning4j.models.glove.GloveWeightLookupTable
-
Deprecated.
- setMaxCount(double) - Method in class org.deeplearning4j.spark.models.embeddings.glove.GloveParam
-
- setMaxIter(int) - Method in class org.deeplearning4j.plot.BarnesHutTsne.Builder
-
- setMaxIter(int) - Method in class org.deeplearning4j.plot.Tsne.Builder
-
- setMaxIterations(int) - Method in class org.deeplearning4j.optimize.solvers.BackTrackLineSearch
-
- setMean(double) - Method in class org.deeplearning4j.nn.conf.distribution.LogNormalDistribution
-
- setMean(double) - Method in class org.deeplearning4j.nn.conf.distribution.NormalDistribution
-
- setMean(double) - Method in class org.deeplearning4j.nn.conf.distribution.TruncatedNormalDistribution
-
- setMessageHandlerClass(String) - Method in class org.deeplearning4j.spark.parameterserver.conf.SharedTrainingConfiguration
-
- setMessageHandlerClass(MessageHandler) - Method in class org.deeplearning4j.spark.parameterserver.conf.SharedTrainingConfiguration
-
- setMinAlpha(double) - Method in class org.deeplearning4j.spark.models.embeddings.word2vec.Word2VecParam.Builder
-
Deprecated.
- setMinAlpha(double) - Method in class org.deeplearning4j.spark.models.embeddings.word2vec.Word2VecParam
-
Deprecated.
- setMinAlpha(double) - Method in class org.deeplearning4j.spark.models.embeddings.word2vec.Word2VecPerformerVoid
-
Deprecated.
- setMinWordFrequency(int) - Method in class org.deeplearning4j.bagofwords.vectorizer.BagOfWordsVectorizer.Builder
-
- setMinWordFrequency(int) - Method in class org.deeplearning4j.bagofwords.vectorizer.TfidfVectorizer.Builder
-
- setMode(MagicQueue.Mode) - Method in class org.deeplearning4j.parallelism.MagicQueue.Builder
-
Deprecated.
- setModelExporter(SparkModelExporter<T>) - Method in class org.deeplearning4j.spark.models.sequencevectors.SparkSequenceVectors.Builder
-
- setModelExporter(SparkModelExporter<VocabWord>) - Method in class org.deeplearning4j.spark.models.word2vec.SparkWord2Vec.Builder
-
This method defines the way model will be exported after training is finished
- setModelUtils(ModelUtils) - Method in interface org.deeplearning4j.models.embeddings.wordvectors.WordVectors
-
Specifies ModelUtils to be used to access model
- setModelUtils(ModelUtils) - Method in class org.deeplearning4j.models.embeddings.wordvectors.WordVectorsImpl
-
- setModelUtils(ModelUtils) - Method in class org.deeplearning4j.models.word2vec.StaticWord2Vec
-
Specifies ModelUtils to be used to access model
PLEASE NOTE: This method has no effect in this implementation.
- setMomentum(double) - Method in class org.deeplearning4j.plot.BarnesHutTsne.Builder
-
- setMomentum(double) - Method in class org.deeplearning4j.plot.Tsne.Builder
-
- setName(String) - Method in class org.ansj.app.keyword.Keyword
-
- setName(String) - Method in class org.ansj.domain.NewWord
-
- setName(String) - Method in class org.ansj.domain.Term
-
- setNature(Nature) - Method in class org.ansj.domain.NewWord
-
- setNature(Nature) - Method in class org.ansj.domain.Term
-
- setNatureStrToArray(String) - Static method in class org.ansj.domain.TermNature
-
- setNegative(double) - Method in class org.deeplearning4j.models.embeddings.inmemory.InMemoryLookupTable
-
- setNegative(double) - Method in class org.deeplearning4j.spark.models.embeddings.glove.GloveParam
-
- setNegative(double) - Method in class org.deeplearning4j.spark.models.embeddings.word2vec.Word2VecParam
-
Deprecated.
- setNegative(double) - Method in class org.deeplearning4j.spark.models.embeddings.word2vec.Word2VecPerformerVoid
-
Deprecated.
- setNetwork(ComputationGraph) - Method in class org.deeplearning4j.spark.impl.graph.SparkComputationGraph
-
- setNetwork(MultiLayerNetwork) - Method in class org.deeplearning4j.spark.impl.multilayer.SparkDl4jMultiLayer
-
Set the network that underlies this SparkDl4jMultiLayer instacne
- setNewWord(boolean) - Method in class org.ansj.domain.Term
-
- setNext(Term) - Method in class org.ansj.domain.Term
-
返回他自己
- setNextRandom(AtomicLong) - Method in class org.deeplearning4j.spark.models.embeddings.word2vec.Word2VecParam.Builder
-
Deprecated.
- setNextRandom(AtomicLong) - Method in class org.deeplearning4j.spark.models.embeddings.word2vec.Word2VecParam
-
Deprecated.
- setNextRandom(AtomicLong) - Method in class org.deeplearning4j.spark.models.embeddings.word2vec.Word2VecPerformerVoid
-
Deprecated.
- setNGrams(int) - Method in class org.deeplearning4j.spark.models.embeddings.word2vec.Word2Vec.Builder
-
Specifies N of n-Grams :)
- setNIn(InputType, boolean) - Method in class org.deeplearning4j.nn.conf.layers.ActivationLayer
-
- setNIn(InputType, boolean) - Method in class org.deeplearning4j.nn.conf.layers.BaseRecurrentLayer
-
- setNIn(InputType, boolean) - Method in class org.deeplearning4j.nn.conf.layers.BaseUpsamplingLayer
-
- setNIn(InputType, boolean) - Method in class org.deeplearning4j.nn.conf.layers.BatchNormalization
-
- setNIn(InputType, boolean) - Method in class org.deeplearning4j.nn.conf.layers.CnnLossLayer
-
- setNIn(InputType, boolean) - Method in class org.deeplearning4j.nn.conf.layers.Convolution1DLayer
-
- setNIn(InputType, boolean) - Method in class org.deeplearning4j.nn.conf.layers.Convolution3D
-
- setNIn(InputType, boolean) - Method in class org.deeplearning4j.nn.conf.layers.ConvolutionLayer
-
- setNIn(InputType, boolean) - Method in class org.deeplearning4j.nn.conf.layers.DropoutLayer
-
- setNIn(InputType, boolean) - Method in class org.deeplearning4j.nn.conf.layers.FeedForwardLayer
-
- setNIn(InputType, boolean) - Method in class org.deeplearning4j.nn.conf.layers.GlobalPoolingLayer
-
- setNIn(InputType, boolean) - Method in class org.deeplearning4j.nn.conf.layers.Layer
-
Set the nIn value (number of inputs, or input channels for CNNs) based on the given input type
- setNIn(InputType, boolean) - Method in class org.deeplearning4j.nn.conf.layers.LocalResponseNormalization
-
- setNIn(InputType, boolean) - Method in class org.deeplearning4j.nn.conf.layers.misc.FrozenLayer
-
- setNIn(InputType, boolean) - Method in class org.deeplearning4j.nn.conf.layers.NoParamLayer
-
- setNIn(InputType, boolean) - Method in class org.deeplearning4j.nn.conf.layers.objdetect.Yolo2OutputLayer
-
- setNIn(InputType, boolean) - Method in class org.deeplearning4j.nn.conf.layers.recurrent.Bidirectional
-
- setNIn(InputType, boolean) - Method in class org.deeplearning4j.nn.conf.layers.RnnLossLayer
-
- setNIn(InputType, boolean) - Method in class org.deeplearning4j.nn.conf.layers.RnnOutputLayer
-
- setNIn(InputType, boolean) - Method in class org.deeplearning4j.nn.conf.layers.samediff.AbstractSameDiffLayer
-
- setNIn(InputType, boolean) - Method in class org.deeplearning4j.nn.conf.layers.samediff.BaseSameDiffLayer
-
- setNIn(InputType, boolean) - Method in class org.deeplearning4j.nn.conf.layers.SpaceToBatchLayer
-
- setNIn(InputType, boolean) - Method in class org.deeplearning4j.nn.conf.layers.SpaceToDepthLayer
-
- setNIn(InputType, boolean) - Method in class org.deeplearning4j.nn.conf.layers.Subsampling1DLayer
-
- setNIn(InputType, boolean) - Method in class org.deeplearning4j.nn.conf.layers.Subsampling3DLayer
-
- setNIn(InputType, boolean) - Method in class org.deeplearning4j.nn.conf.layers.SubsamplingLayer
-
- setNIn(InputType, boolean) - Method in class org.deeplearning4j.nn.conf.layers.util.MaskLayer
-
- setNIn(InputType, boolean) - Method in class org.deeplearning4j.nn.conf.layers.util.MaskZeroLayer
-
- setNIn(InputType, boolean) - Method in class org.deeplearning4j.nn.conf.layers.wrapper.BaseWrapperLayer
-
- setNIn(InputType, boolean) - Method in class org.deeplearning4j.nn.conf.layers.ZeroPadding1DLayer
-
- setNIn(InputType, boolean) - Method in class org.deeplearning4j.nn.conf.layers.ZeroPadding3DLayer
-
- setNoEdgeHandling(NoEdgeHandling) - Method in class org.deeplearning4j.models.sequencevectors.graph.walkers.impl.PopularityWalker.Builder
-
This method defines walker behavior when it gets to node which has no next nodes available
Default value: RESTART_ON_DISCONNECTED
- setNoEdgeHandling(NoEdgeHandling) - Method in class org.deeplearning4j.models.sequencevectors.graph.walkers.impl.RandomWalker.Builder
-
This method defines walker behavior when it gets to node which has no next nodes available
Default value: RESTART_ON_DISCONNECTED
- setNoEdgeHandling(NoEdgeHandling) - Method in class org.deeplearning4j.models.sequencevectors.graph.walkers.impl.WeightedWalker.Builder
-
This method defines walker behavior when it gets to node which has no next nodes available
Default value: RESTART_ON_DISCONNECTED
- setNoLeverageOverride(String) - Method in class org.deeplearning4j.nn.workspace.LayerWorkspaceMgr
-
- setNorthEast(QuadTree) - Method in class org.deeplearning4j.clustering.quadtree.QuadTree
-
- setNorthWest(QuadTree) - Method in class org.deeplearning4j.clustering.quadtree.QuadTree
-
- setNumberOfBuckets(int) - Method in class org.deeplearning4j.parallelism.MagicQueue.Builder
-
Deprecated.
- setNumChildren(int) - Method in class org.deeplearning4j.clustering.sptree.SpTree
-
- setNumDimensions(int) - Method in class org.deeplearning4j.plot.BarnesHutTsne
-
- setNumWords(int) - Method in class org.deeplearning4j.spark.models.embeddings.word2vec.Word2VecParam
-
Deprecated.
- setNumWords(int) - Method in class org.deeplearning4j.spark.models.embeddings.word2vec.Word2VecPerformerVoid
-
Deprecated.
- setNumWords(int) - Method in class org.deeplearning4j.ui.nearestneighbors.word2vec.NearestNeighborsQuery
-
- setOffe(int) - Method in class org.ansj.domain.Term
-
- setOutputBatches(List<INDArray[]>) - Method in interface org.deeplearning4j.parallelism.inference.InferenceObservable
-
- setOutputBatches(List<INDArray[]>) - Method in class org.deeplearning4j.parallelism.inference.observers.BasicInferenceObservable
-
- setOutputBatches(List<INDArray[]>) - Method in class org.deeplearning4j.parallelism.inference.observers.BatchedInferenceObservable
-
- setOutputException(Exception) - Method in interface org.deeplearning4j.parallelism.inference.InferenceObservable
-
- setOutputException(Exception) - Method in class org.deeplearning4j.parallelism.inference.observers.BasicInferenceObservable
-
- setOutputs(String...) - Method in class org.deeplearning4j.nn.conf.ComputationGraphConfiguration.GraphBuilder
-
Set the network output labels.
- setOutputs(String...) - Method in class org.deeplearning4j.nn.transferlearning.TransferLearning.GraphBuilder
-
Set outputs to the computation graph, will add to ones that are existing
Also determines the order, like in ComputationGraphConfiguration
- setOutputVertex(boolean) - Method in class org.deeplearning4j.nn.graph.vertex.BaseWrapperVertex
-
- setOutputVertex(boolean) - Method in interface org.deeplearning4j.nn.graph.vertex.GraphVertex
-
Set the GraphVertex to be an output vertex
- setOutputVertices(VertexIndices[]) - Method in class org.deeplearning4j.nn.graph.vertex.BaseGraphVertex
-
- setOutputVertices(VertexIndices[]) - Method in class org.deeplearning4j.nn.graph.vertex.BaseWrapperVertex
-
- setOutputVertices(VertexIndices[]) - Method in interface org.deeplearning4j.nn.graph.vertex.GraphVertex
-
set the output vertices.
- setParam(String, INDArray) - Method in interface org.deeplearning4j.nn.api.Model
-
Set the parameter with a new ndarray
- setParam(String, INDArray) - Method in class org.deeplearning4j.nn.graph.ComputationGraph
-
- setParam(String, INDArray) - Method in class org.deeplearning4j.nn.layers.AbstractLayer
-
- setParam(String, INDArray) - Method in class org.deeplearning4j.nn.layers.BaseLayer
-
- setParam(String, INDArray) - Method in class org.deeplearning4j.nn.layers.recurrent.BidirectionalLayer
-
- setParam(String, INDArray) - Method in class org.deeplearning4j.nn.layers.samediff.SameDiffLayer
-
- setParam(String, INDArray) - Method in class org.deeplearning4j.nn.layers.variational.VariationalAutoencoder
-
- setParam(String, INDArray) - Method in class org.deeplearning4j.nn.layers.wrapper.BaseWrapperLayer
-
- setParam(String, INDArray) - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
-
- setParam(String, INDArray) - Method in class org.deeplearning4j.plot.BarnesHutTsne
-
- setParam(Broadcast<Word2VecParam>) - Method in class org.deeplearning4j.spark.models.embeddings.word2vec.Word2VecFuncCall
-
Deprecated.
- setParameters(INDArray) - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
-
Sets parameters for the model.
- setParameters(Map<String, Map>) - Method in class org.deeplearning4j.ui.weights.beans.CompactModelAndGradient
-
- setParameterServerConfiguration(VoidConfiguration) - Method in class org.deeplearning4j.spark.models.sequencevectors.SparkSequenceVectors.Builder
-
- setParameterServerConfiguration(VoidConfiguration) - Method in class org.deeplearning4j.spark.models.word2vec.SparkWord2Vec.Builder
-
- setParamMagnitudes(List<Map<String, List<Double>>>) - Method in class org.deeplearning4j.ui.weights.beans.CompactModelAndGradient
-
- setParams(Set<String>) - Method in interface org.deeplearning4j.nn.api.layers.LayerConstraint
-
Set the parameters that this layer constraint should be applied to
- setParams(INDArray) - Method in interface org.deeplearning4j.nn.api.Model
-
Set the parameters for this model.
- setParams(INDArray) - Method in class org.deeplearning4j.nn.graph.ComputationGraph
-
- setParams(INDArray) - Method in class org.deeplearning4j.nn.layers.AbstractLayer
-
- setParams(INDArray, char) - Method in class org.deeplearning4j.nn.layers.AbstractLayer
-
- setParams(INDArray) - Method in class org.deeplearning4j.nn.layers.BaseLayer
-
- setParams(INDArray, char) - Method in class org.deeplearning4j.nn.layers.BaseLayer
-
- setParams(INDArray) - Method in class org.deeplearning4j.nn.layers.BasePretrainNetwork
-
- setParams(INDArray) - Method in class org.deeplearning4j.nn.layers.convolution.ConvolutionLayer
-
- setParams(INDArray) - Method in class org.deeplearning4j.nn.layers.convolution.SpaceToBatch
-
- setParams(INDArray) - Method in class org.deeplearning4j.nn.layers.convolution.SpaceToDepth
-
- setParams(INDArray) - Method in class org.deeplearning4j.nn.layers.convolution.subsampling.Subsampling3DLayer
-
- setParams(INDArray) - Method in class org.deeplearning4j.nn.layers.convolution.subsampling.SubsamplingLayer
-
- setParams(INDArray) - Method in class org.deeplearning4j.nn.layers.convolution.upsampling.Upsampling2D
-
- setParams(INDArray) - Method in class org.deeplearning4j.nn.layers.convolution.upsampling.Upsampling3D
-
- setParams(INDArray) - Method in class org.deeplearning4j.nn.layers.normalization.LocalResponseNormalization
-
- setParams(INDArray) - Method in class org.deeplearning4j.nn.layers.recurrent.BidirectionalLayer
-
- setParams(INDArray) - Method in class org.deeplearning4j.nn.layers.samediff.SameDiffLayer
-
- setParams(INDArray, char) - Method in class org.deeplearning4j.nn.layers.samediff.SameDiffLayer
-
- setParams(INDArray) - Method in class org.deeplearning4j.nn.layers.variational.VariationalAutoencoder
-
- setParams(INDArray) - Method in class org.deeplearning4j.nn.layers.wrapper.BaseWrapperLayer
-
- setParams(INDArray) - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
-
Set the parameters for this model.
- setParams(INDArray) - Method in class org.deeplearning4j.plot.BarnesHutTsne
-
- setParamsViewArray(INDArray) - Method in interface org.deeplearning4j.nn.api.Model
-
Set the initial parameters array as a view of the full (backprop) network parameters
NOTE: this is intended to be used internally in MultiLayerNetwork and ComputationGraph, not by users.
- setParamsViewArray(INDArray) - Method in class org.deeplearning4j.nn.graph.ComputationGraph
-
- setParamsViewArray(INDArray) - Method in class org.deeplearning4j.nn.layers.AbstractLayer
-
- setParamsViewArray(INDArray) - Method in class org.deeplearning4j.nn.layers.BaseLayer
-
- setParamsViewArray(INDArray) - Method in class org.deeplearning4j.nn.layers.recurrent.BidirectionalLayer
-
- setParamsViewArray(INDArray) - Method in class org.deeplearning4j.nn.layers.samediff.SameDiffLayer
-
- setParamsViewArray(INDArray) - Method in class org.deeplearning4j.nn.layers.variational.VariationalAutoencoder
-
- setParamsViewArray(INDArray) - Method in class org.deeplearning4j.nn.layers.wrapper.BaseWrapperLayer
-
- setParamsViewArray(INDArray) - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
-
- setParamsViewArray(INDArray) - Method in class org.deeplearning4j.plot.BarnesHutTsne
-
- setParamTable(Map<String, INDArray>) - Method in interface org.deeplearning4j.nn.api.Model
-
Setter for the param table
- setParamTable(Map<String, INDArray>) - Method in class org.deeplearning4j.nn.graph.ComputationGraph
-
- setParamTable(Map<String, INDArray>) - Method in class org.deeplearning4j.nn.layers.AbstractLayer
-
- setParamTable(Map<String, INDArray>) - Method in class org.deeplearning4j.nn.layers.BaseLayer
-
- setParamTable(Map<String, INDArray>) - Method in class org.deeplearning4j.nn.layers.recurrent.BidirectionalLayer
-
- setParamTable(Map<String, INDArray>) - Method in class org.deeplearning4j.nn.layers.samediff.SameDiffLayer
-
- setParamTable(Map<String, INDArray>) - Method in class org.deeplearning4j.nn.layers.variational.VariationalAutoencoder
-
- setParamTable(Map<String, INDArray>) - Method in class org.deeplearning4j.nn.layers.wrapper.BaseWrapperLayer
-
- setParamTable(Map<String, INDArray>) - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
-
- setParamTable(Map<String, INDArray>) - Method in class org.deeplearning4j.plot.BarnesHutTsne
-
- setParent(KDTree.KDNode) - Method in class org.deeplearning4j.clustering.kdtree.KDTree.KDNode
-
- setParent(QuadTree) - Method in class org.deeplearning4j.clustering.quadtree.QuadTree
-
- setParent(Tree) - Method in class org.deeplearning4j.nn.layers.feedforward.autoencoder.recursive.Tree
-
- setParse(String) - Method in class org.deeplearning4j.nn.layers.feedforward.autoencoder.recursive.Tree
-
- setPassword(String) - Method in class org.deeplearning4j.ui.UiConnectionInfo.Builder
-
- setPath(String) - Method in class org.deeplearning4j.ui.UiConnectionInfo.Builder
-
If you're using UiServer as servlet, located not at root folder of webserver (i.e.
- setPath(String) - Method in class org.deeplearning4j.ui.weights.beans.CompactModelAndGradient
-
- setPathCost(int) - Method in class com.atilika.kuromoji.viterbi.ViterbiNode
-
param cost minimum path cost found this far
- setPathScore(Term, Map<String, Double>) - Method in class org.ansj.domain.Term
-
核心构建最优的路径
- setPathSelfScore(Term) - Method in class org.ansj.domain.Term
-
核心分数的最优的路径,越小越好
- setPersonNatureAttr(PersonNatureAttr) - Method in class org.ansj.domain.TermNatures
-
- setPointLocationChange(AtomicInteger) - Method in class org.deeplearning4j.clustering.info.ClusterSetInfo
-
- setPoints(List<Integer>) - Method in class org.deeplearning4j.models.sequencevectors.sequence.SequenceElement
-
Sets Huffman tree points
- setPoints(int[]) - Method in class org.deeplearning4j.models.sequencevectors.sequence.SequenceElement
-
Sets Huffman tree points
- setPopularityMode(PopularityMode) - Method in class org.deeplearning4j.models.sequencevectors.graph.walkers.impl.PopularityWalker.Builder
-
This method defines which nodes should be taken in account when choosing next hope: maximum popularity, lowest popularity, or average popularity.
- setPopularitySpread(int) - Method in class org.deeplearning4j.models.sequencevectors.graph.walkers.impl.PopularityWalker.Builder
-
This method defines, how much nodes should take place in next hop selection.
- setPort(int) - Method in class org.deeplearning4j.ui.UiConnectionInfo.Builder
-
- setPosition(int) - Method in class org.deeplearning4j.parallelism.inference.observers.BatchedInferenceObservable
-
- setPrediction(INDArray) - Method in class org.deeplearning4j.nn.layers.feedforward.autoencoder.recursive.Tree
-
- setPreProcessor(DataSetPreProcessor) - Method in class org.deeplearning4j.datasets.datavec.RecordReaderDataSetIterator
-
- setPreProcessor(MultiDataSetPreProcessor) - Method in class org.deeplearning4j.datasets.datavec.RecordReaderMultiDataSetIterator
-
- setPreProcessor(DataSetPreProcessor) - Method in class org.deeplearning4j.datasets.datavec.SequenceRecordReaderDataSetIterator
-
- setPreProcessor(DataSetPreProcessor) - Method in class org.deeplearning4j.datasets.iterator.AbstractDataSetIterator
-
Set a pre processor
- setPreProcessor(DataSetPreProcessor) - Method in class org.deeplearning4j.datasets.iterator.AsyncDataSetIterator
-
Set a pre processor
- setPreProcessor(MultiDataSetPreProcessor) - Method in class org.deeplearning4j.datasets.iterator.AsyncMultiDataSetIterator
-
Set the preprocessor to be applied to each MultiDataSet, before each MultiDataSet is returned.
- setPreProcessor(DataSetPreProcessor) - Method in class org.deeplearning4j.datasets.iterator.AsyncShieldDataSetIterator
-
Set a pre processor
- setPreProcessor(MultiDataSetPreProcessor) - Method in class org.deeplearning4j.datasets.iterator.AsyncShieldMultiDataSetIterator
-
Set the preprocessor to be applied to each MultiDataSet, before each MultiDataSet is returned.
- setPreProcessor(DataSetPreProcessor) - Method in class org.deeplearning4j.datasets.iterator.BaseDatasetIterator
-
- setPreProcessor(DataSetPreProcessor) - Method in class org.deeplearning4j.datasets.iterator.EarlyTerminationDataSetIterator
-
- setPreProcessor(MultiDataSetPreProcessor) - Method in class org.deeplearning4j.datasets.iterator.EarlyTerminationMultiDataSetIterator
-
- setPreProcessor(DataSetPreProcessor) - Method in class org.deeplearning4j.datasets.iterator.ExistingDataSetIterator
-
- setPreProcessor(DataSetPreProcessor) - Method in class org.deeplearning4j.datasets.iterator.FileSplitDataSetIterator
-
- setPreProcessor(DataSetPreProcessor) - Method in class org.deeplearning4j.datasets.iterator.impl.BenchmarkDataSetIterator
-
- setPreProcessor(MultiDataSetPreProcessor) - Method in class org.deeplearning4j.datasets.iterator.impl.BenchmarkMultiDataSetIterator
-
- setPreProcessor(DataSetPreProcessor) - Method in class org.deeplearning4j.datasets.iterator.impl.ListDataSetIterator
-
- setPreProcessor(MultiDataSetPreProcessor) - Method in class org.deeplearning4j.datasets.iterator.impl.MultiDataSetIteratorAdapter
-
- setPreProcessor(MultiDataSetPreProcessor) - Method in class org.deeplearning4j.datasets.iterator.impl.SingletonMultiDataSetIterator
-
- setPreProcessor(DataSetPreProcessor) - Method in class org.deeplearning4j.datasets.iterator.IteratorDataSetIterator
-
- setPreProcessor(MultiDataSetPreProcessor) - Method in class org.deeplearning4j.datasets.iterator.IteratorMultiDataSetIterator
-
- setPreProcessor(DataSetPreProcessor) - Method in class org.deeplearning4j.datasets.iterator.MultiDataSetWrapperIterator
-
- setPreProcessor(DataSetPreProcessor) - Method in class org.deeplearning4j.datasets.iterator.MultipleEpochsIterator
-
Deprecated.
- setPreProcessor(DataSetPreProcessor) - Method in class org.deeplearning4j.datasets.iterator.parallel.BaseParallelDataSetIterator
-
- setPreProcessor(DataSetPreProcessor) - Method in class org.deeplearning4j.datasets.iterator.ReconstructionDataSetIterator
-
- setPreProcessor(DataSetPreProcessor) - Method in class org.deeplearning4j.datasets.iterator.SamplingDataSetIterator
-
- setPreProcessor(DataSetPreProcessor) - Method in class org.deeplearning4j.datasets.iterator.WorkspacesShieldDataSetIterator
-
- setPreProcessor(DataSetPreProcessor) - Method in class org.deeplearning4j.datasets.test.TestDataSetIterator
-
- setPreProcessor(DataSetPreProcessor) - Method in class org.deeplearning4j.iterator.CnnSentenceDataSetIterator
-
- setPreProcessor(DataSetPreProcessor) - Method in class org.deeplearning4j.models.word2vec.iterator.Word2VecDataSetIterator
-
- setPreProcessor(DataSetPreProcessor) - Method in class org.deeplearning4j.spark.iterator.BaseDataSetIterator
-
- setPreProcessor(MultiDataSetPreProcessor) - Method in class org.deeplearning4j.spark.iterator.PathSparkMultiDataSetIterator
-
- setPreProcessor(MultiDataSetPreProcessor) - Method in class org.deeplearning4j.spark.iterator.PortableDataStreamMultiDataSetIterator
-
- setPreProcessor(DataSetPreProcessor) - Method in class org.deeplearning4j.spark.parameterserver.iterators.VirtualDataSetIterator
-
- setPreProcessor(MultiDataSetPreProcessor) - Method in class org.deeplearning4j.spark.parameterserver.iterators.VirtualMultiDataSetIterator
-
- setPreProcessor(SentencePreProcessor) - Method in class org.deeplearning4j.text.sentenceiterator.AggregatingSentenceIterator
-
- setPreProcessor(SentencePreProcessor) - Method in class org.deeplearning4j.text.sentenceiterator.BaseSentenceIterator
-
- setPreProcessor(SentencePreProcessor) - Method in class org.deeplearning4j.text.sentenceiterator.BasicLineIterator
-
- setPreProcessor(SentencePreProcessor) - Method in class org.deeplearning4j.text.sentenceiterator.BasicResultSetIterator
-
- setPreProcessor(SentencePreProcessor) - Method in class org.deeplearning4j.text.sentenceiterator.MutipleEpochsSentenceIterator
-
- setPreProcessor(SentencePreProcessor) - Method in class org.deeplearning4j.text.sentenceiterator.PrefetchingSentenceIterator
-
Deprecated.
- setPreProcessor(SentencePreProcessor) - Method in interface org.deeplearning4j.text.sentenceiterator.SentenceIterator
-
- setPreProcessor(SentencePreProcessor) - Method in class org.deeplearning4j.text.sentenceiterator.StreamLineIterator.Builder
-
- setPreProcessor(SentencePreProcessor) - Method in class org.deeplearning4j.text.sentenceiterator.StreamLineIterator
-
- setPreProcessor(SentencePreProcessor) - Method in class org.deeplearning4j.text.sentenceiterator.SynchronizedSentenceIterator
-
- setProbabilityOfSuccess(double) - Method in class org.deeplearning4j.nn.conf.distribution.BinomialDistribution
-
- setProperties(Object, Properties) - Static method in class org.deeplearning4j.util.Dl4jReflection
-
Sets the properties of the given object
- setRDDVarMap(JavaRDD<String>, Broadcast<Map<String, Object>>) - Method in class org.deeplearning4j.spark.text.functions.TextPipeline
-
- setRealMin(double) - Method in class org.deeplearning4j.plot.BarnesHutTsne.Builder
-
- setRealMin(double) - Method in class org.deeplearning4j.plot.Tsne.Builder
-
- setRealName(String) - Method in class org.ansj.domain.Term
-
- setRealName(Graph, List<Term>) - Method in class org.ansj.splitWord.Analysis
-
将为标准化的词语设置到分词中
- setRegion(Regions) - Method in class org.deeplearning4j.aws.ec2.Ec2BoxCreator
-
- setRelTolx(double) - Method in class org.deeplearning4j.optimize.solvers.BackTrackLineSearch
-
Sets the tolerance of relative diff in function value.
- setRestartProbability(double) - Method in class org.deeplearning4j.models.sequencevectors.graph.walkers.impl.PopularityWalker.Builder
-
This method defines a chance for walk restart
Good value would be somewhere between 0.03-0.07
- setRestartProbability(double) - Method in class org.deeplearning4j.models.sequencevectors.graph.walkers.impl.RandomWalker.Builder
-
This method defines a chance for walk restart
Good value would be somewhere between 0.03-0.07
- setRestartProbability(double) - Method in class org.deeplearning4j.models.sequencevectors.graph.walkers.impl.WeightedWalker.Builder
-
This method defines a chance for walk restart
Good value would be somewhere between 0.03-0.07
- setRight(PatriciaTrie.PatriciaNode<V>) - Method in class com.atilika.kuromoji.trie.PatriciaTrie.PatriciaNode
-
Set this node's right node
- setRight(KDTree.KDNode) - Method in class org.deeplearning4j.clustering.kdtree.KDTree.KDNode
-
- setRounding(int) - Method in class org.deeplearning4j.ui.weights.HistogramBin.Builder
-
Sets number of numbers behind decimal part
- setSamplingMode(SamplingMode) - Method in class org.deeplearning4j.models.sequencevectors.graph.walkers.impl.NearestVertexWalker.Builder
-
This method defines sorting which will be used to generate walks.
- setScavengerActivationThreshold(int) - Method in class org.deeplearning4j.models.word2vec.wordstore.VocabularyHolder
-
This method is needed ONLY for unit tests and should NOT be available in public scope.
- setScore(double) - Method in class org.ansj.app.keyword.Keyword
-
- setScore(double) - Method in class org.ansj.domain.NewWord
-
- setScore(NatureRecognition.NatureTerm) - Method in class org.ansj.recognition.impl.NatureRecognition.NatureTerm
-
- setScore(double) - Method in class org.deeplearning4j.nn.graph.ComputationGraph
-
- setScore(double) - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
-
- setScore(double) - Method in class org.deeplearning4j.spark.impl.graph.SparkComputationGraph
-
- setScore(double) - Method in class org.deeplearning4j.spark.impl.multilayer.SparkDl4jMultiLayer
-
- setScore(double) - Method in class org.deeplearning4j.ui.weights.beans.CompactModelAndGradient
-
- setScoreFor(INDArray, LayerWorkspaceMgr) - Method in class org.deeplearning4j.optimize.solvers.BackTrackLineSearch
-
- setScores(List<Double>) - Method in class org.deeplearning4j.ui.weights.beans.CompactModelAndGradient
-
- setScoreWithZ(INDArray) - Method in class org.deeplearning4j.nn.layers.BaseLayer
-
- setScoreWithZ(INDArray) - Method in class org.deeplearning4j.nn.layers.BaseOutputLayer
-
- setScoreWithZ(INDArray) - Method in class org.deeplearning4j.nn.layers.BasePretrainNetwork
-
- setScoreWithZ(INDArray) - Method in class org.deeplearning4j.nn.layers.LossLayer
-
- setScoreWithZ(INDArray) - Method in class org.deeplearning4j.nn.layers.training.CenterLossOutputLayer
-
- setSeed(long) - Method in class org.deeplearning4j.models.sequencevectors.graph.walkers.impl.NearestVertexWalker.Builder
-
- setSeed(long) - Method in class org.deeplearning4j.models.sequencevectors.graph.walkers.impl.PopularityWalker.Builder
-
This method specifies random seed.
- setSeed(long) - Method in class org.deeplearning4j.models.sequencevectors.graph.walkers.impl.RandomWalker.Builder
-
This method specifies random seed.
- setSeed(long) - Method in class org.deeplearning4j.models.sequencevectors.graph.walkers.impl.WeightedWalker.Builder
-
This method specifies random seed.
- setSeed(long, int) - Method in class org.deeplearning4j.spark.models.embeddings.word2vec.VocabHolder
-
- setSentence(List<VocabWord>) - Method in class org.deeplearning4j.spark.models.embeddings.word2vec.Word2VecFuncCall
-
Deprecated.
- setSentenceIterator(SentenceIterator) - Method in class org.deeplearning4j.models.word2vec.Word2Vec
-
This method defines SentenceIterator instance, that will be used as training corpus source
- setSentencePreProcessor(SentencePreProcessor) - Method in class org.deeplearning4j.text.sentenceiterator.PrefetchingSentenceIterator.Builder
-
Deprecated.
- setSequenceIterator(SequenceIterator<VocabWord>) - Method in class org.deeplearning4j.models.paragraphvectors.ParagraphVectors
-
This method defines SequenceIterator instance, that will be used as training corpus source.
- setSequenceIterator(SequenceIterator<VocabWord>) - Method in class org.deeplearning4j.models.word2vec.Word2Vec
-
This method defines SequenceIterator instance, that will be used as training corpus source.
- setSequenceLabel(T) - Method in class org.deeplearning4j.models.sequencevectors.sequence.Sequence
-
Set sequence label
- setSequenceLabels(List<T>) - Method in class org.deeplearning4j.models.sequencevectors.sequence.Sequence
-
Sets sequence labels
- setSequenceLearningAlgorithm(SparkSequenceLearningAlgorithm) - Method in class org.deeplearning4j.spark.models.sequencevectors.SparkSequenceVectors.Builder
-
- setSequenceLearningAlgorithm(SparkSequenceLearningAlgorithm) - Method in class org.deeplearning4j.spark.models.word2vec.SparkWord2Vec.Builder
-
- setSequencesCount(long) - Method in class org.deeplearning4j.models.sequencevectors.sequence.SequenceElement
-
This method sets documents count to specified value
- setSerializedModelFileName(String) - Method in class org.deeplearning4j.nn.modelexport.solr.ltr.model.ScoringModel
-
- setSessionID(String) - Method in interface org.deeplearning4j.api.storage.listener.RoutingIterationListener
-
- setSessionID(String) - Method in class org.deeplearning4j.ui.stats.BaseStatsListener
-
- setSessionId(String) - Method in class org.deeplearning4j.ui.UiConnectionInfo.Builder
-
This method allows you to specify sessionId for this UiConnectionInfo instance
PLEASE NOTE: This is not recommended.
- setSessionId(String) - Method in class org.deeplearning4j.ui.UiConnectionInfo
-
- setSimiarlityFunction(String) - Method in class org.deeplearning4j.plot.BarnesHutTsne
-
- setSize(int) - Method in class org.deeplearning4j.clustering.quadtree.QuadTree
-
- setSouthEast(QuadTree) - Method in class org.deeplearning4j.clustering.quadtree.QuadTree
-
- setSouthWest(QuadTree) - Method in class org.deeplearning4j.clustering.quadtree.QuadTree
-
- setSpreadSpectrum(SpreadSpectrum) - Method in class org.deeplearning4j.models.sequencevectors.graph.walkers.impl.PopularityWalker.Builder
-
This method allows you to define, if nodes within popularity spread should have equal chances to be picked for next hop, or they should have chances proportional to their popularity.
- setStateViewArray(Layer, INDArray, boolean) - Method in interface org.deeplearning4j.nn.api.Updater
-
Set the internal (historical) state view array for this updater
- setStateViewArray(INDArray) - Method in class org.deeplearning4j.nn.updater.BaseMultiLayerUpdater
-
Set the view array.
- setStateViewArray(Layer, INDArray, boolean) - Method in class org.deeplearning4j.nn.updater.BaseMultiLayerUpdater
-
- setStats(SparkTrainingStats) - Method in interface org.deeplearning4j.spark.api.TrainingResult
-
- setStats(SparkTrainingStats) - Method in class org.deeplearning4j.spark.impl.paramavg.ParameterAveragingTrainingResult
-
- setStats(SparkTrainingStats) - Method in class org.deeplearning4j.spark.parameterserver.training.SharedTrainingResult
-
- setStatsStorage(StatsStorageRouter) - Method in class org.deeplearning4j.ui.module.remote.RemoteReceiverModule
-
- setStd(double) - Method in class org.deeplearning4j.nn.conf.distribution.LogNormalDistribution
-
- setStd(double) - Method in class org.deeplearning4j.nn.conf.distribution.NormalDistribution
-
- setStd(double) - Method in class org.deeplearning4j.nn.conf.distribution.TruncatedNormalDistribution
-
- setStem(boolean) - Method in class org.deeplearning4j.models.word2vec.VocabWork
-
- setStem(Token, String) - Method in class org.deeplearning4j.text.annotator.StemmerAnnotator
-
- setStepMax(double) - Method in class org.deeplearning4j.optimize.solvers.BackTrackLineSearch
-
- setStopWords(Collection<String>) - Method in class org.deeplearning4j.bagofwords.vectorizer.BagOfWordsVectorizer.Builder
-
- setStopWords(Collection<String>) - Method in class org.deeplearning4j.bagofwords.vectorizer.TfidfVectorizer.Builder
-
- setStopWords(Collection<String>) - Method in class org.deeplearning4j.models.word2vec.wordstore.VocabConstructor.Builder
-
- setStorageLevel(StorageLevel) - Method in class org.deeplearning4j.spark.models.sequencevectors.SparkSequenceVectors.Builder
-
- setStorageLevel(StorageLevel) - Method in class org.deeplearning4j.spark.models.word2vec.SparkWord2Vec.Builder
-
- setStorageRouter(StatsStorageRouter) - Method in interface org.deeplearning4j.api.storage.listener.RoutingIterationListener
-
- setStorageRouter(StatsStorageRouter) - Method in class org.deeplearning4j.ui.stats.BaseStatsListener
-
- setStr(String) - Method in interface org.ansj.splitWord.GetWords
-
同一个对象传入词语
- setStr(String) - Method in class org.ansj.splitWord.impl.GetWordsImpl
-
- setSubTerm(List<Term>) - Method in class org.ansj.domain.Term
-
- setSwitchMomentumIteration(int) - Method in class org.deeplearning4j.plot.BarnesHutTsne.Builder
-
- setSwitchMomentumIteration(int) - Method in class org.deeplearning4j.plot.Tsne.Builder
-
- setSyn0(INDArray) - Method in class org.deeplearning4j.models.embeddings.inmemory.InMemoryLookupTable
-
- setSyn1(INDArray) - Method in class org.deeplearning4j.models.embeddings.inmemory.InMemoryLookupTable
-
- setSyn1Neg(INDArray) - Method in class org.deeplearning4j.models.embeddings.inmemory.InMemoryLookupTable
-
- setSynonyms(List<String>) - Method in class org.ansj.domain.Term
-
- setTable(INDArray) - Method in class org.deeplearning4j.models.embeddings.inmemory.InMemoryLookupTable
-
- setTable(INDArray) - Method in class org.deeplearning4j.spark.models.embeddings.word2vec.Word2VecParam
-
Deprecated.
- setTable(INDArray) - Method in class org.deeplearning4j.spark.models.embeddings.word2vec.Word2VecPerformerVoid
-
Deprecated.
- setTableId(Long) - Method in interface org.deeplearning4j.models.embeddings.WeightLookupTable
-
Set's table Id.
- setTags(List<String>) - Method in class org.deeplearning4j.nn.layers.feedforward.autoencoder.recursive.Tree
-
- setTargetFolder(String) - Method in class org.deeplearning4j.models.sequencevectors.listeners.SerializingListener.Builder
-
This method specifies target folder where models should be saved
- setTargetFolder(File) - Method in class org.deeplearning4j.models.sequencevectors.listeners.SerializingListener.Builder
-
This method specifies target folder where models should be saved
- setTargetVocabCache(VocabCache<T>) - Method in class org.deeplearning4j.models.word2vec.wordstore.VocabConstructor.Builder
-
After temporary internal vocabulary is built, it will be transferred to target VocabCache you pass here
- setTemplate(int[][]) - Method in class org.ansj.app.crf.Config
-
- setTermination(boolean) - Method in class org.deeplearning4j.parallelism.EarlyStoppingParallelTrainer
-
- setTerminationReason(IterationTerminationCondition) - Method in class org.deeplearning4j.parallelism.EarlyStoppingParallelTrainer
-
- setTerms(List<Term>) - Method in class org.ansj.domain.Result
-
- setTo(Term) - Method in class org.ansj.domain.Term
-
- setToAndfrom(Term, Term) - Static method in class org.ansj.util.TermUtil
-
- setTokenizerFactory(TokenizerFactory) - Method in class org.deeplearning4j.bagofwords.vectorizer.BagOfWordsVectorizer.Builder
-
- setTokenizerFactory(TokenizerFactory) - Method in class org.deeplearning4j.bagofwords.vectorizer.TfidfVectorizer.Builder
-
- setTokenizerFactory(TokenizerFactory) - Method in class org.deeplearning4j.models.word2vec.Word2Vec
-
This method defines TokenizerFactory instance to be using during model building
- setTokenizerFactory(TokenizerFactory) - Method in class org.deeplearning4j.spark.models.word2vec.SparkWord2Vec.Builder
-
This method defines tokenizer htat will be used for corpus tokenization
- setTokenPreProcessor(TokenPreProcess) - Method in class org.deeplearning4j.text.tokenization.tokenizer.ChineseTokenizer
-
- setTokenPreProcessor(TokenPreProcess) - Method in class org.deeplearning4j.text.tokenization.tokenizer.DefaultStreamTokenizer
-
- setTokenPreProcessor(TokenPreProcess) - Method in class org.deeplearning4j.text.tokenization.tokenizer.DefaultTokenizer
-
- setTokenPreProcessor(TokenPreProcess) - Method in class org.deeplearning4j.text.tokenization.tokenizer.JapaneseTokenizer
-
- setTokenPreProcessor(TokenPreProcess) - Method in class org.deeplearning4j.text.tokenization.tokenizer.KoreanTokenizer
-
- setTokenPreProcessor(TokenPreProcess) - Method in class org.deeplearning4j.text.tokenization.tokenizer.NGramTokenizer
-
- setTokenPreProcessor(TokenPreProcess) - Method in class org.deeplearning4j.text.tokenization.tokenizer.PosUimaTokenizer
-
- setTokenPreProcessor(TokenPreProcess) - Method in interface org.deeplearning4j.text.tokenization.tokenizer.Tokenizer
-
Set the token pre process
- setTokenPreProcessor(TokenPreProcess) - Method in class org.deeplearning4j.text.tokenization.tokenizer.UimaTokenizer
-
- setTokenPreProcessor(TokenPreProcess) - Method in class org.deeplearning4j.text.tokenization.tokenizerFactory.ChineseTokenizerFactory
-
- setTokenPreProcessor(TokenPreProcess) - Method in class org.deeplearning4j.text.tokenization.tokenizerfactory.DefaultTokenizerFactory
-
- setTokenPreProcessor(TokenPreProcess) - Method in class org.deeplearning4j.text.tokenization.tokenizerfactory.JapaneseTokenizerFactory
-
- setTokenPreProcessor(TokenPreProcess) - Method in class org.deeplearning4j.text.tokenization.tokenizerfactory.KoreanTokenizerFactory
-
- setTokenPreProcessor(TokenPreProcess) - Method in class org.deeplearning4j.text.tokenization.tokenizerfactory.NGramTokenizerFactory
-
- setTokenPreProcessor(TokenPreProcess) - Method in class org.deeplearning4j.text.tokenization.tokenizerfactory.PosUimaTokenizerFactory
-
- setTokenPreProcessor(TokenPreProcess) - Method in interface org.deeplearning4j.text.tokenization.tokenizerfactory.TokenizerFactory
-
Sets a token pre processor to be used
with every tokenizer
- setTokenPreProcessor(TokenPreProcess) - Method in class org.deeplearning4j.text.tokenization.tokenizerfactory.UimaTokenizerFactory
-
- setTokens(Map<String, VocabWord>) - Method in class org.deeplearning4j.models.word2vec.wordstore.inmemory.InMemoryLookupCache
-
Deprecated.
- setTokens(List<String>) - Method in class org.deeplearning4j.nn.layers.feedforward.autoencoder.recursive.Tree
-
- setTotalWords(int) - Method in class org.deeplearning4j.spark.models.embeddings.word2vec.Word2VecParam
-
Deprecated.
- setTotalWords(int) - Method in class org.deeplearning4j.spark.models.embeddings.word2vec.Word2VecPerformerVoid
-
Deprecated.
- setTWM - Variable in class org.deeplearning4j.nn.conf.NeuralNetConfiguration.Builder
-
- setType(String) - Method in class org.deeplearning4j.nn.layers.feedforward.autoencoder.recursive.Tree
-
- setType(MagicQueue.Type) - Method in class org.deeplearning4j.parallelism.MagicQueue.Builder
-
Deprecated.
- setUncaughtExceptionHandler(Thread.UncaughtExceptionHandler) - Method in interface org.deeplearning4j.parallelism.trainer.Trainer
-
- setUNK(String) - Method in interface org.deeplearning4j.models.embeddings.wordvectors.WordVectors
-
- setUNK(String) - Method in class org.deeplearning4j.models.sequencevectors.SequenceVectors
-
- setUNK(String) - Method in class org.deeplearning4j.models.word2vec.StaticWord2Vec
-
- setUnk(T) - Method in class org.deeplearning4j.models.word2vec.wordstore.VocabConstructor.Builder
-
- setup(ClusteringStrategy) - Static method in class org.deeplearning4j.clustering.algorithm.BaseClusteringAlgorithm
-
- setup(int, int, String, boolean) - Static method in class org.deeplearning4j.clustering.kmeans.KMeansClustering
-
Setup a kmeans instance
- setup(int, double, String, boolean, boolean) - Static method in class org.deeplearning4j.clustering.kmeans.KMeansClustering
-
- setup(int, int, String) - Static method in class org.deeplearning4j.clustering.kmeans.KMeansClustering
-
Setup a kmeans instance
- setup(int, double, String, boolean) - Static method in class org.deeplearning4j.clustering.kmeans.KMeansClustering
-
- setup(int, String, boolean) - Static method in class org.deeplearning4j.clustering.strategy.FixedClusterCountStrategy
-
- setup(int, String) - Static method in class org.deeplearning4j.clustering.strategy.OptimisationStrategy
-
- setup(SparkConf) - Method in class org.deeplearning4j.spark.models.embeddings.word2vec.Word2VecPerformer
-
Deprecated.
- setup(SparkConf) - Method in class org.deeplearning4j.spark.models.embeddings.word2vec.Word2VecPerformerVoid
-
Deprecated.
- setUpdateConfig(StatsUpdateConfiguration) - Method in class org.deeplearning4j.ui.stats.BaseStatsListener
-
- setUpdateMagnitudes(List<Map<String, List<Double>>>) - Method in class org.deeplearning4j.ui.weights.beans.CompactModelAndGradient
-
- setUpdater(ComputationGraphUpdater) - Method in class org.deeplearning4j.nn.graph.ComputationGraph
-
Set the computationGraphUpdater for the network
- setUpdater(Updater) - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
-
Set the updater for the MultiLayerNetwork
- setUpdater(Updater) - Method in interface org.deeplearning4j.optimize.api.ConvexOptimizer
-
- setUpdater(Updater) - Method in class org.deeplearning4j.optimize.solvers.BaseOptimizer
-
- setUpdaterComputationGraph(ComputationGraphUpdater) - Method in interface org.deeplearning4j.optimize.api.ConvexOptimizer
-
- setUpdaterComputationGraph(ComputationGraphUpdater) - Method in class org.deeplearning4j.optimize.solvers.BaseOptimizer
-
- setupIfNeccessary() - Method in class org.deeplearning4j.parallelism.trainer.DefaultTrainer
-
- setUpper(double) - Method in class org.deeplearning4j.nn.conf.distribution.UniformDistribution
-
- setupSearchState(Pair<Gradient, Double>) - Method in interface org.deeplearning4j.optimize.api.ConvexOptimizer
-
Based on the gradient and score
setup a search state
- setupSearchState(Pair<Gradient, Double>) - Method in class org.deeplearning4j.optimize.solvers.BaseOptimizer
-
Setup the initial search state
- setupSearchState(Pair<Gradient, Double>) - Method in class org.deeplearning4j.optimize.solvers.LBFGS
-
- setUseAdaGrad(boolean) - Method in class org.deeplearning4j.models.embeddings.inmemory.InMemoryLookupTable
-
- setUseAdaGrad(boolean) - Method in class org.deeplearning4j.spark.models.embeddings.glove.GloveParam
-
- setUseAdaGrad(boolean) - Method in class org.deeplearning4j.spark.models.embeddings.word2vec.Word2VecParam
-
Deprecated.
- setUseAdaGrad(boolean) - Method in class org.deeplearning4j.spark.models.embeddings.word2vec.Word2VecPerformerVoid
-
Deprecated.
- setUseHS(boolean) - Method in class org.deeplearning4j.models.embeddings.inmemory.InMemoryLookupTable
-
- SetUtils - Class in org.deeplearning4j.clustering.util
-
- setV(V) - Method in class org.ansj.domain.KV
-
- setValue(V) - Method in class com.atilika.kuromoji.trie.PatriciaTrie.PatriciaNode
-
Sets this node's value
- setValue(double) - Method in class org.deeplearning4j.nn.conf.distribution.ConstantDistribution
-
- setValue(String) - Method in class org.deeplearning4j.nn.layers.feedforward.autoencoder.recursive.Tree
-
- setVector(INDArray) - Method in class org.deeplearning4j.nn.layers.feedforward.autoencoder.recursive.Tree
-
- setVectorLength(int) - Method in class org.deeplearning4j.models.embeddings.inmemory.InMemoryLookupTable
-
- setVectorLength(int) - Method in class org.deeplearning4j.spark.models.embeddings.glove.GloveParam
-
- setVectorLength(int) - Method in class org.deeplearning4j.spark.models.embeddings.word2vec.Word2VecParam.Builder
-
Deprecated.
- setVectorLength(int) - Method in class org.deeplearning4j.spark.models.embeddings.word2vec.Word2VecParam
-
Deprecated.
- setVectorLength(int) - Method in class org.deeplearning4j.spark.models.embeddings.word2vec.Word2VecPerformerVoid
-
Deprecated.
- setVectorsListeners(Collection<VectorsListener<VocabWord>>) - Method in class org.deeplearning4j.models.glove.Glove.Builder
-
This method sets VectorsListeners for this SequenceVectors model
- setVectorsListeners(Collection<VectorsListener<V>>) - Method in class org.deeplearning4j.models.node2vec.Node2Vec.Builder
-
Deprecated.
- setVectorsListeners(Collection<VectorsListener<VocabWord>>) - Method in class org.deeplearning4j.models.paragraphvectors.ParagraphVectors.Builder
-
This method sets VectorsListeners for this SequenceVectors model
- setVectorsListeners(Collection<VectorsListener<T>>) - Method in class org.deeplearning4j.models.sequencevectors.SequenceVectors.Builder
-
This method sets VectorsListeners for this SequenceVectors model
- setVectorsListeners(Collection<VectorsListener<VocabWord>>) - Method in class org.deeplearning4j.models.word2vec.Word2Vec.Builder
-
This method sets VectorsListeners for this SequenceVectors model
- setVertexVectors(INDArray) - Method in class org.deeplearning4j.graph.models.embeddings.InMemoryGraphLookupTable
-
- setVocab(VocabCache<VocabWord>) - Method in class org.deeplearning4j.bagofwords.vectorizer.BagOfWordsVectorizer.Builder
-
- setVocab(VocabCache<VocabWord>) - Method in class org.deeplearning4j.bagofwords.vectorizer.TfidfVectorizer.Builder
-
- setVocab(VocabCache) - Method in class org.deeplearning4j.models.embeddings.inmemory.InMemoryLookupTable
-
- setVocab(VocabCache) - Method in class org.deeplearning4j.models.embeddings.wordvectors.WordVectorsImpl
-
- setVocabCache(VocabCache<T>) - Method in class org.deeplearning4j.models.sequencevectors.transformers.impl.GraphTransformer.Builder
-
- setVocabs(Map<String, VocabWord>) - Method in class org.deeplearning4j.models.word2vec.wordstore.inmemory.InMemoryLookupCache
-
Deprecated.
- setW1(VocabWord) - Method in class org.deeplearning4j.spark.models.embeddings.glove.GloveChange
-
- setW1BiasHistory(double) - Method in class org.deeplearning4j.spark.models.embeddings.glove.GloveChange
-
- setW1BiasUpdate(double) - Method in class org.deeplearning4j.spark.models.embeddings.glove.GloveChange
-
- setW1History(INDArray) - Method in class org.deeplearning4j.spark.models.embeddings.glove.GloveChange
-
- setW1Update(INDArray) - Method in class org.deeplearning4j.spark.models.embeddings.glove.GloveChange
-
- setW2(VocabWord) - Method in class org.deeplearning4j.spark.models.embeddings.glove.GloveChange
-
- setW2BiasHistory(double) - Method in class org.deeplearning4j.spark.models.embeddings.glove.GloveChange
-
- setW2BiasUpdate(double) - Method in class org.deeplearning4j.spark.models.embeddings.glove.GloveChange
-
- setW2History(INDArray) - Method in class org.deeplearning4j.spark.models.embeddings.glove.GloveChange
-
- setW2Update(INDArray) - Method in class org.deeplearning4j.spark.models.embeddings.glove.GloveChange
-
- setWalkDirection(WalkDirection) - Method in class org.deeplearning4j.models.sequencevectors.graph.walkers.impl.PopularityWalker.Builder
-
This method defines next hop selection within walk
- setWalkDirection(WalkDirection) - Method in class org.deeplearning4j.models.sequencevectors.graph.walkers.impl.RandomWalker.Builder
-
This method defines next hop selection within walk
- setWalkDirection(WalkDirection) - Method in class org.deeplearning4j.models.sequencevectors.graph.walkers.impl.WeightedWalker.Builder
-
This method defines next hop selection within walk
- setWalkLength(int) - Method in class org.deeplearning4j.models.sequencevectors.graph.walkers.impl.NearestVertexWalker.Builder
-
This method defines maximal number of nodes to be visited during walk.
- setWalkLength(int) - Method in class org.deeplearning4j.models.sequencevectors.graph.walkers.impl.PopularityWalker.Builder
-
This method specifies output sequence (walk) length
- setWalkLength(int) - Method in class org.deeplearning4j.models.sequencevectors.graph.walkers.impl.RandomWalker.Builder
-
This method specifies output sequence (walk) length
- setWalkLength(int) - Method in class org.deeplearning4j.models.sequencevectors.graph.walkers.impl.WeightedWalker.Builder
-
This method specifies output sequence (walk) length
- setWeights(Map<String, INDArray>) - Method in class org.deeplearning4j.nn.modelimport.keras.KerasLayer
-
Set weights for Keras layer.
- setWeights(Map<String, INDArray>) - Method in class org.deeplearning4j.nn.modelimport.keras.layers.convolutional.KerasConvolution
-
Set weights for layer.
- setWeights(Map<String, INDArray>) - Method in class org.deeplearning4j.nn.modelimport.keras.layers.convolutional.KerasConvolution1D
-
Set weights for layer.
- setWeights(Map<String, INDArray>) - Method in class org.deeplearning4j.nn.modelimport.keras.layers.convolutional.KerasDepthwiseConvolution2D
-
Set weights for layer.
- setWeights(Map<String, INDArray>) - Method in class org.deeplearning4j.nn.modelimport.keras.layers.convolutional.KerasSeparableConvolution2D
-
Set weights for layer.
- setWeights(Map<String, INDArray>) - Method in class org.deeplearning4j.nn.modelimport.keras.layers.core.KerasDense
-
Set weights for layer.
- setWeights(Map<String, INDArray>) - Method in class org.deeplearning4j.nn.modelimport.keras.layers.embeddings.KerasEmbedding
-
Set weights for layer.
- setWeights(Map<String, INDArray>) - Method in class org.deeplearning4j.nn.modelimport.keras.layers.normalization.KerasBatchNormalization
-
Set weights for layer.
- setWeights(Map<String, INDArray>) - Method in class org.deeplearning4j.nn.modelimport.keras.layers.recurrent.KerasLstm
-
Set weights for layer.
- setWeights(Map<String, INDArray>) - Method in class org.deeplearning4j.nn.modelimport.keras.layers.recurrent.KerasSimpleRnn
-
Set weights for layer.
- setWeights(Map<String, INDArray>) - Method in class org.deeplearning4j.nn.modelimport.keras.layers.wrappers.KerasBidirectional
-
Set weights for Bidirectional layer.
- setWeights(InMemoryLookupTable) - Method in class org.deeplearning4j.spark.models.embeddings.word2vec.Word2VecParam
-
Deprecated.
- setWeights(InMemoryLookupTable) - Method in class org.deeplearning4j.spark.models.embeddings.word2vec.Word2VecPerformerVoid
-
Deprecated.
- setWidth(int, double) - Method in class org.deeplearning4j.clustering.sptree.Cell
-
- setWidth(INDArray) - Method in class org.deeplearning4j.clustering.sptree.Cell
-
- setWindow(int) - Method in class org.deeplearning4j.spark.models.embeddings.word2vec.Word2VecParam
-
Deprecated.
- setWindow(int) - Method in class org.deeplearning4j.spark.models.embeddings.word2vec.Word2VecPerformerVoid
-
Deprecated.
- setWord(String) - Method in class org.deeplearning4j.models.word2vec.VocabWord
-
- setWord(String) - Method in class org.deeplearning4j.ui.nearestneighbors.word2vec.NearestNeighborsQuery
-
- setWordCount(Broadcast<AtomicLong>) - Method in class org.deeplearning4j.spark.models.embeddings.word2vec.Word2VecParam
-
Deprecated.
- setWordCount(Broadcast<AtomicLong>) - Method in class org.deeplearning4j.spark.models.embeddings.word2vec.Word2VecPerformerVoid
-
Deprecated.
- setWordFrequencies(Counter<String>) - Method in class org.deeplearning4j.models.word2vec.wordstore.inmemory.InMemoryLookupCache
-
Deprecated.
- setWords(List<String>) - Method in class org.deeplearning4j.text.movingwindow.Window
-
- setWordsSeen(Long) - Method in class org.deeplearning4j.spark.models.embeddings.word2vec.Word2VecFuncCall
-
Deprecated.
- setWordsSeen(AtomicLong) - Method in class org.deeplearning4j.spark.models.embeddings.word2vec.Word2VecParam
-
Deprecated.
- setWork(String) - Method in class org.deeplearning4j.models.word2vec.VocabWork
-
- setWorkerID(String) - Method in interface org.deeplearning4j.api.storage.listener.RoutingIterationListener
-
- setWorkerID(String) - Method in class org.deeplearning4j.ui.stats.BaseStatsListener
-
- setWorkspaceMode(WorkspaceMode) - Method in class org.deeplearning4j.nn.transferlearning.TransferLearning.GraphBuilder
-
- setX(double) - Method in class org.deeplearning4j.clustering.quadtree.Cell
-
- setxMax(double) - Method in class org.deeplearning4j.models.glove.GloveWeightLookupTable
-
Deprecated.
- setxMax(double) - Method in class org.deeplearning4j.spark.models.embeddings.glove.GloveParam
-
- setXMax(Double) - Method in class org.deeplearning4j.ui.components.chart.Chart.Builder
-
Used to override/set the maximum value for the x axis.
- setXMin(Double) - Method in class org.deeplearning4j.ui.components.chart.Chart.Builder
-
Used to override/set the minimum value for the x axis.
- setXValues(double[]) - Method in class org.deeplearning4j.ui.components.chart.ChartStackedArea.Builder
-
Set the x-axis values
- setY(double) - Method in class org.deeplearning4j.clustering.quadtree.Cell
-
- setYMax(Double) - Method in class org.deeplearning4j.ui.components.chart.Chart.Builder
-
Used to override/set the maximum value for the y axis.
- setYMin(Double) - Method in class org.deeplearning4j.ui.components.chart.Chart.Builder
-
Used to override/set the minimum value for the y axis.
- shakeFrequency - Variable in class org.deeplearning4j.optimize.solvers.accumulation.EncodingHandler
-
- shakeFrequency - Variable in class org.deeplearning4j.spark.parameterserver.conf.SharedTrainingConfiguration
-
- shakeFrequency - Variable in class org.deeplearning4j.spark.parameterserver.training.SharedTrainingMaster.Builder
-
- shakeFrequency(int) - Method in class org.deeplearning4j.spark.parameterserver.training.SharedTrainingMaster.Builder
-
During NN training, each X iterations, executors will send encoded dense updates with lower threshold.
- shakeFrequency - Variable in class org.deeplearning4j.spark.parameterserver.training.SharedTrainingMaster
-
- ShallowSequenceElement - Class in org.deeplearning4j.models.sequencevectors.sequence
-
This is special shallow SequenceElement implementation, that doesn't hold labels or any other custom user-defined data
- ShallowSequenceElement(double, long) - Constructor for class org.deeplearning4j.models.sequencevectors.sequence.ShallowSequenceElement
-
- shallowVocabBroadcast - Variable in class org.deeplearning4j.spark.models.sequencevectors.functions.DistributedFunction
-
- shallowVocabCache - Variable in class org.deeplearning4j.spark.models.sequencevectors.functions.DistributedFunction
-
- shallowVocabCache - Variable in class org.deeplearning4j.spark.models.sequencevectors.functions.PartitionTrainingFunction
-
- shallowVocabCache - Variable in class org.deeplearning4j.spark.models.sequencevectors.functions.TrainingFunction
-
- shallowVocabCache - Variable in class org.deeplearning4j.spark.models.sequencevectors.SparkSequenceVectors
-
- shallowVocabCacheBroadcast - Variable in class org.deeplearning4j.spark.models.sequencevectors.SparkSequenceVectors
-
- shape - Variable in class org.deeplearning4j.optimize.solvers.accumulation.BasicGradientsAccumulator
-
- SharedFlatMapDataSet<R extends TrainingResult> - Class in org.deeplearning4j.spark.parameterserver.functions
-
- SharedFlatMapDataSet(TrainingWorker<R>) - Constructor for class org.deeplearning4j.spark.parameterserver.functions.SharedFlatMapDataSet
-
- SharedFlatMapMultiDataSet<R extends TrainingResult> - Class in org.deeplearning4j.spark.parameterserver.functions
-
Created by raver119 on 13.06.17.
- SharedFlatMapMultiDataSet(TrainingWorker<R>) - Constructor for class org.deeplearning4j.spark.parameterserver.functions.SharedFlatMapMultiDataSet
-
- SharedFlatMapMultiPDS<R extends TrainingResult> - Class in org.deeplearning4j.spark.parameterserver.functions
-
Created by raver119 on 14.06.17.
- SharedFlatMapMultiPDS(TrainingWorker<R>) - Constructor for class org.deeplearning4j.spark.parameterserver.functions.SharedFlatMapMultiPDS
-
- SharedFlatMapMultiPDS(TrainingWorker<R>, PortableDataStreamMDSCallback) - Constructor for class org.deeplearning4j.spark.parameterserver.functions.SharedFlatMapMultiPDS
-
- SharedFlatMapPaths<R extends TrainingResult> - Class in org.deeplearning4j.spark.parameterserver.functions
-
- SharedFlatMapPaths(TrainingWorker<R>) - Constructor for class org.deeplearning4j.spark.parameterserver.functions.SharedFlatMapPaths
-
- SharedFlatMapPathsMDS<R extends TrainingResult> - Class in org.deeplearning4j.spark.parameterserver.functions
-
- SharedFlatMapPathsMDS(TrainingWorker<R>) - Constructor for class org.deeplearning4j.spark.parameterserver.functions.SharedFlatMapPathsMDS
-
- SharedFlatMapPDS<R extends TrainingResult> - Class in org.deeplearning4j.spark.parameterserver.functions
-
- SharedFlatMapPDS(TrainingWorker<R>) - Constructor for class org.deeplearning4j.spark.parameterserver.functions.SharedFlatMapPDS
-
- SharedFlatMapPDS(TrainingWorker<R>, PortableDataStreamCallback) - Constructor for class org.deeplearning4j.spark.parameterserver.functions.SharedFlatMapPDS
-
- SharedGradient - Class in org.deeplearning4j.optimize.listeners
-
- SharedGradient() - Constructor for class org.deeplearning4j.optimize.listeners.SharedGradient
-
- SharedTrainingAccumulationFunction - Class in org.deeplearning4j.spark.parameterserver.accumulation
-
- SharedTrainingAccumulationFunction() - Constructor for class org.deeplearning4j.spark.parameterserver.accumulation.SharedTrainingAccumulationFunction
-
- SharedTrainingAccumulationTuple - Class in org.deeplearning4j.spark.parameterserver.accumulation
-
- SharedTrainingAccumulationTuple() - Constructor for class org.deeplearning4j.spark.parameterserver.accumulation.SharedTrainingAccumulationTuple
-
- SharedTrainingAggregateFunction - Class in org.deeplearning4j.spark.parameterserver.accumulation
-
- SharedTrainingAggregateFunction() - Constructor for class org.deeplearning4j.spark.parameterserver.accumulation.SharedTrainingAggregateFunction
-
- SharedTrainingConfiguration - Class in org.deeplearning4j.spark.parameterserver.conf
-
- SharedTrainingConfiguration() - Constructor for class org.deeplearning4j.spark.parameterserver.conf.SharedTrainingConfiguration
-
- SharedTrainingMaster - Class in org.deeplearning4j.spark.parameterserver.training
-
- SharedTrainingMaster() - Constructor for class org.deeplearning4j.spark.parameterserver.training.SharedTrainingMaster
-
- SharedTrainingMaster(VoidConfiguration, Integer, RDDTrainingApproach, StorageLevel, boolean, RepartitionStrategy, Repartition, double, double, double, double, int, int, int, long, int) - Constructor for class org.deeplearning4j.spark.parameterserver.training.SharedTrainingMaster
-
- SharedTrainingMaster.Builder - Class in org.deeplearning4j.spark.parameterserver.training
-
- SharedTrainingResult - Class in org.deeplearning4j.spark.parameterserver.training
-
- SharedTrainingResult() - Constructor for class org.deeplearning4j.spark.parameterserver.training.SharedTrainingResult
-
- SharedTrainingWorker - Class in org.deeplearning4j.spark.parameterserver.training
-
- SharedTrainingWorker(Broadcast<NetBroadcastTuple>, Broadcast<SharedTrainingConfiguration>) - Constructor for class org.deeplearning4j.spark.parameterserver.training.SharedTrainingWorker
-
- SharedTrainingWrapper - Class in org.deeplearning4j.spark.parameterserver.pw
-
This class maintains ParallelWrapper instance in Spark environment, and provides primitives for inter-executor
communication during training over partitions.
- SharedTrainingWrapper() - Constructor for class org.deeplearning4j.spark.parameterserver.pw.SharedTrainingWrapper
-
- shiftFactor - Variable in class org.deeplearning4j.nn.conf.graph.ShiftVertex
-
- ShiftVertex - Class in org.deeplearning4j.nn.conf.graph
-
A ShiftVertex is used to shift the activations of a single layer
One could use it to add a bias or as part of some other calculation.
- ShiftVertex(double) - Constructor for class org.deeplearning4j.nn.conf.graph.ShiftVertex
-
- ShiftVertex - Class in org.deeplearning4j.nn.graph.vertex.impl
-
A ShiftVertex is used to shift the activations of a single layer
One could use it to add a bias or as part of some other calculation.
- ShiftVertex(ComputationGraph, String, int, double) - Constructor for class org.deeplearning4j.nn.graph.vertex.impl.ShiftVertex
-
- ShiftVertex(ComputationGraph, String, int, VertexIndices[], VertexIndices[], double) - Constructor for class org.deeplearning4j.nn.graph.vertex.impl.ShiftVertex
-
- shouldStop(AtomicBoolean) - Method in class org.deeplearning4j.parallelism.parameterserver.ParameterServerTrainer.ParameterServerTrainerBuilder
-
- shouldStop - Variable in class org.deeplearning4j.parallelism.trainer.DefaultTrainer
-
- shouldUpdate(AtomicBoolean) - Method in class org.deeplearning4j.parallelism.parameterserver.ParameterServerTrainer.ParameterServerTrainerBuilder
-
- shouldUpdate - Variable in class org.deeplearning4j.parallelism.trainer.DefaultTrainer
-
- shouldWork - Variable in class org.deeplearning4j.datasets.iterator.AsyncDataSetIterator
-
- shouldWork - Variable in class org.deeplearning4j.datasets.iterator.AsyncMultiDataSetIterator
-
- shouldWork - Variable in class org.deeplearning4j.parallelism.AsyncIterator
-
- showLegend(boolean) - Method in class org.deeplearning4j.ui.components.chart.Chart.Builder
-
- showMessage(String) - Method in class org.deeplearning4j.aws.ec2.provision.HostProvisioner
-
- shuffle - Variable in class org.deeplearning4j.datasets.fetchers.MnistDataFetcher
-
- shuffle - Variable in class org.deeplearning4j.models.embeddings.learning.impl.elements.GloVe.Builder
-
- shuffle(boolean) - Method in class org.deeplearning4j.models.embeddings.learning.impl.elements.GloVe.Builder
-
Parameter specifying, if cooccurrences list should be shuffled between training epochs
- shuffle(boolean) - Method in class org.deeplearning4j.models.glove.Glove.Builder
-
Parameter specifying, if cooccurrences list should be shuffled between training epochs
- shuffle - Variable in class org.deeplearning4j.models.sequencevectors.transformers.impl.GraphTransformer.Builder
-
- shuffle - Variable in class org.deeplearning4j.models.sequencevectors.transformers.impl.GraphTransformer
-
- shuffleArray(int[], long) - Static method in class org.deeplearning4j.clustering.util.MathUtils
-
- shuffleArray(int[], Random) - Static method in class org.deeplearning4j.clustering.util.MathUtils
-
- shuffleExamples(JavaRDD<DataSet>, int, int) - Static method in class org.deeplearning4j.spark.util.SparkUtils
-
Randomly shuffle the examples in each DataSet object, and recombine them into new DataSet objects
with the specified BatchSize
- shuffleOnReset(boolean) - Method in class org.deeplearning4j.models.sequencevectors.transformers.impl.GraphTransformer.Builder
-
- shutdown() - Method in class org.deeplearning4j.datasets.iterator.AsyncDataSetIterator.AsyncPrefetchThread
-
- shutdown() - Method in class org.deeplearning4j.datasets.iterator.AsyncDataSetIterator
-
This method will terminate background thread AND will destroy attached workspace (if any)
PLEASE NOTE: After shutdown() call, this instance can't be used anymore
- shutdown() - Method in class org.deeplearning4j.datasets.iterator.AsyncMultiDataSetIterator.AsyncPrefetchThread
-
- shutdown() - Method in class org.deeplearning4j.datasets.iterator.AsyncMultiDataSetIterator
-
This method will terminate background thread AND will destroy attached workspace (if any)
PLEASE NOTE: After shutdown() call, this instance can't be used anymore
- shutdown() - Method in class org.deeplearning4j.parallelism.AsyncIterator
-
- shutdown() - Method in class org.deeplearning4j.parallelism.ParallelInference
-
This method gracefully shuts down ParallelInference instance
- shutdown() - Method in class org.deeplearning4j.parallelism.ParallelWrapper
-
This method causes all threads used for parallel training to stop
- shutdown() - Method in class org.deeplearning4j.parallelism.trainer.DefaultTrainer
-
- shutdown() - Method in interface org.deeplearning4j.parallelism.trainer.Trainer
-
Shutdown this worker
- shutdown() - Method in class org.deeplearning4j.text.documentiterator.AsyncLabelAwareIterator
-
- shutdown() - Method in class org.deeplearning4j.text.documentiterator.BasicLabelAwareIterator
-
- shutdown() - Method in class org.deeplearning4j.text.documentiterator.FileLabelAwareIterator
-
- shutdown() - Method in class org.deeplearning4j.text.documentiterator.FilenamesLabelAwareIterator
-
- shutdown() - Method in class org.deeplearning4j.text.documentiterator.interoperability.DocumentIteratorConverter
-
- shutdown() - Method in interface org.deeplearning4j.text.documentiterator.LabelAwareIterator
-
- shutdown() - Method in class org.deeplearning4j.text.documentiterator.SimpleLabelAwareIterator
-
- shutdown() - Method in class org.deeplearning4j.text.sentenceiterator.interoperability.SentenceIteratorConverter
-
- sigmoid(double) - Static method in class org.deeplearning4j.clustering.util.MathUtils
-
1 / 1 + exp(-x)
- SilentIntroductoryConfirmation - Class in org.deeplearning4j.spark.parameterserver.networking.messages
-
- SilentIntroductoryConfirmation() - Constructor for class org.deeplearning4j.spark.parameterserver.networking.messages.SilentIntroductoryConfirmation
-
- SilentIntroductoryMessage - Class in org.deeplearning4j.spark.parameterserver.networking.messages
-
- SilentIntroductoryMessage() - Constructor for class org.deeplearning4j.spark.parameterserver.networking.messages.SilentIntroductoryMessage
-
- SilentIntroductoryMessage(String, int) - Constructor for class org.deeplearning4j.spark.parameterserver.networking.messages.SilentIntroductoryMessage
-
- SilentTrainingDriver - Class in org.deeplearning4j.spark.parameterserver.networking
-
This TrainingDriver implementation is suited ONLY for Spark Master, and handles application & redistribution of incoming encoded messages across distributed network
- SilentTrainingDriver(GradientsAccumulator) - Constructor for class org.deeplearning4j.spark.parameterserver.networking.SilentTrainingDriver
-
- SilentTrainingDriver(INDArray, StepFunction) - Constructor for class org.deeplearning4j.spark.parameterserver.networking.SilentTrainingDriver
-
- SilentUpdatesMessage - Class in org.deeplearning4j.spark.parameterserver.networking.messages
-
- SilentUpdatesMessage() - Constructor for class org.deeplearning4j.spark.parameterserver.networking.messages.SilentUpdatesMessage
-
- SilentUpdatesMessage(INDArray, long) - Constructor for class org.deeplearning4j.spark.parameterserver.networking.messages.SilentUpdatesMessage
-
- similarity(Vertex<V>, Vertex<V>) - Method in class org.deeplearning4j.graph.models.embeddings.GraphVectorsImpl
-
Returns the cosine similarity of the vector representations of two vertices in the graph
- similarity(int, int) - Method in class org.deeplearning4j.graph.models.embeddings.GraphVectorsImpl
-
Returns the cosine similarity of the vector representations of two vertices in the graph,
given the indices of these verticies
- similarity(Vertex<V>, Vertex<V>) - Method in interface org.deeplearning4j.graph.models.GraphVectors
-
- similarity(int, int) - Method in interface org.deeplearning4j.graph.models.GraphVectors
-
- similarity(String, String) - Method in class org.deeplearning4j.models.embeddings.reader.impl.BasicModelUtils
-
Returns the similarity of 2 words.
- similarity(String, String) - Method in interface org.deeplearning4j.models.embeddings.reader.ModelUtils
-
This method implementations should return distance between two given elements
- similarity(String, String) - Method in interface org.deeplearning4j.models.embeddings.wordvectors.WordVectors
-
Returns the similarity of 2 words
- similarity(String, String) - Method in class org.deeplearning4j.models.embeddings.wordvectors.WordVectorsImpl
-
Returns similarity of two elements, provided by ModelUtils
- similarity(String, String) - Method in class org.deeplearning4j.models.word2vec.StaticWord2Vec
-
Returns the similarity of 2 words
- SimilarityComparator() - Constructor for class org.deeplearning4j.models.embeddings.reader.impl.BasicModelUtils.SimilarityComparator
-
- similarityFunction(String) - Method in class org.deeplearning4j.plot.BarnesHutTsne.Builder
-
- SimilarityListener<T extends SequenceElement> - Class in org.deeplearning4j.models.sequencevectors.listeners
-
Simple listener, to monitor similarity between selected elements during training
- SimilarityListener(ListenerEvent, int, String, String) - Constructor for class org.deeplearning4j.models.sequencevectors.listeners.SimilarityListener
-
- similarityToLabel(String, String) - Method in class org.deeplearning4j.models.paragraphvectors.ParagraphVectors
-
Deprecated.
- similarityToLabel(LabelledDocument, String) - Method in class org.deeplearning4j.models.paragraphvectors.ParagraphVectors
-
This method returns similarity of the document to specific label, based on mean value
- similarityToLabel(List<VocabWord>, String) - Method in class org.deeplearning4j.models.paragraphvectors.ParagraphVectors
-
This method returns similarity of the document to specific label, based on mean value
- similarWordsInVocabTo(String, double) - Method in class org.deeplearning4j.models.embeddings.reader.impl.BasicModelUtils
-
Find all words with a similar characters
in the vocab
- similarWordsInVocabTo(String, double) - Method in interface org.deeplearning4j.models.embeddings.reader.ModelUtils
-
Find all words with a similar characters
in the vocab
- similarWordsInVocabTo(String, double) - Method in interface org.deeplearning4j.models.embeddings.wordvectors.WordVectors
-
Find all words with a similar characters
in the vocab
- similarWordsInVocabTo(String, double) - Method in class org.deeplearning4j.models.embeddings.wordvectors.WordVectorsImpl
-
Find all words with a similar characters
in the vocab
- similarWordsInVocabTo(String, double) - Method in class org.deeplearning4j.models.word2vec.StaticWord2Vec
-
Find all words with a similar characters
in the vocab
PLEASE NOTE: This method is not available in this implementation.
- SimpleCNN - Class in org.deeplearning4j.zoo.model
-
A simple convolutional network for generic image classification.
- SimpleLabelAwareIterator - Class in org.deeplearning4j.text.documentiterator
-
This class provide option to build LabelAwareIterator from Iterable or Iterator objects
PLEASE NOTE: This iterator is meant to be used with externally-originated data via Java Iterable/Iterator interface.
- SimpleLabelAwareIterator(Iterable<LabelledDocument>) - Constructor for class org.deeplearning4j.text.documentiterator.SimpleLabelAwareIterator
-
Builds LabelAwareIterator instance using Iterable object
- SimpleLabelAwareIterator(Iterator<LabelledDocument>) - Constructor for class org.deeplearning4j.text.documentiterator.SimpleLabelAwareIterator
-
Builds LabelAwareIterator instance using Iterator object
PLEASE NOTE: If instance is built using Iterator object, reset() method becomes unavailable
- SimpleResourceResolver - Class in com.atilika.kuromoji.util
-
- SimpleResourceResolver(Class<?>) - Constructor for class com.atilika.kuromoji.util.SimpleResourceResolver
-
- SimpleRnn - Class in org.deeplearning4j.nn.conf.layers.recurrent
-
Simple RNN - aka "vanilla" RNN is the simplest type of recurrent neural network layer.
- SimpleRnn(SimpleRnn.Builder) - Constructor for class org.deeplearning4j.nn.conf.layers.recurrent.SimpleRnn
-
- SimpleRnn - Class in org.deeplearning4j.nn.layers.recurrent
-
Simple RNN - aka "vanilla" RNN is the simplest type of recurrent neural network layer.
- SimpleRnn(NeuralNetConfiguration) - Constructor for class org.deeplearning4j.nn.layers.recurrent.SimpleRnn
-
- SimpleRnn.Builder - Class in org.deeplearning4j.nn.conf.layers.recurrent
-
- SimpleRnnParamInitializer - Class in org.deeplearning4j.nn.params
-
- SimpleRnnParamInitializer() - Constructor for class org.deeplearning4j.nn.params.SimpleRnnParamInitializer
-
- SingletonMultiDataSetIterator - Class in org.deeplearning4j.datasets.iterator.impl
-
A very simple adapter class for converting a single MultiDataSet to a MultiDataSetIterator.
- SingletonMultiDataSetIterator(MultiDataSet) - Constructor for class org.deeplearning4j.datasets.iterator.impl.SingletonMultiDataSetIterator
-
- SingleToPairFunction<T> - Class in org.deeplearning4j.spark.impl.multilayer.scoring
-
- SingleToPairFunction() - Constructor for class org.deeplearning4j.spark.impl.multilayer.scoring.SingleToPairFunction
-
- size() - Method in class com.atilika.kuromoji.trie.PatriciaTrie
-
Returns the number of key-value mappings in this trie
- size() - Method in class org.ansj.domain.Result
-
- size() - Method in class org.deeplearning4j.clustering.kdtree.KDTree
-
The number of elements in the tree
- size() - Method in class org.deeplearning4j.models.glove.count.CountMap
-
- size() - Method in class org.deeplearning4j.models.sequencevectors.sequence.Sequence
-
This method returns number of elements in this sequence
- size - Variable in class org.deeplearning4j.nn.conf.layers.BaseUpsamplingLayer
-
- size - Variable in class org.deeplearning4j.nn.conf.layers.BaseUpsamplingLayer.UpsamplingBuilder
-
- size(int) - Method in class org.deeplearning4j.nn.conf.layers.Upsampling1D.Builder
-
Upsampling size int
- size(int[]) - Method in class org.deeplearning4j.nn.conf.layers.Upsampling1D.Builder
-
Upsampling size int array with a single element
- size - Variable in class org.deeplearning4j.nn.conf.layers.Upsampling1D
-
- size(int) - Method in class org.deeplearning4j.nn.conf.layers.Upsampling2D.Builder
-
Upsampling size int, used for both height and width
- size(int[]) - Method in class org.deeplearning4j.nn.conf.layers.Upsampling2D.Builder
-
Upsampling size array
- size - Variable in class org.deeplearning4j.nn.conf.layers.Upsampling2D
-
- size(int) - Method in class org.deeplearning4j.nn.conf.layers.Upsampling3D.Builder
-
Upsampling size as int, so same upsampling size is used for depth, width and height
- size(int[]) - Method in class org.deeplearning4j.nn.conf.layers.Upsampling3D.Builder
-
Upsampling size as int, so same upsampling size is used for depth, width and height
- size - Variable in class org.deeplearning4j.nn.conf.layers.Upsampling3D
-
- size() - Method in class org.deeplearning4j.optimize.solvers.accumulation.FancyBlockingQueue
-
- size() - Method in class org.deeplearning4j.parallelism.ConcurrentHashSet
-
Deprecated.
- size() - Method in class org.deeplearning4j.parallelism.MagicQueue
-
Deprecated.
This method returns average queue size for all devices
- size(int) - Method in class org.deeplearning4j.parallelism.MagicQueue
-
Deprecated.
- size() - Method in class org.deeplearning4j.text.documentiterator.LabelsSource
-
- size() - Method in class org.deeplearning4j.util.DiskBasedQueue
-
- sizeInBytes - Variable in class org.deeplearning4j.nn.layers.BaseCudnnHelper
-
- sizeOf(T) - Method in class org.deeplearning4j.datasets.iterator.file.BaseFileIterator
-
- sizeOf(DataSet) - Method in class org.deeplearning4j.datasets.iterator.file.FileDataSetIterator
-
- sizeOf(MultiDataSet) - Method in class org.deeplearning4j.datasets.iterator.file.FileMultiDataSetIterator
-
- skipDueToPretrainConfig() - Method in class org.deeplearning4j.nn.updater.UpdaterBlock
-
- SkipGram<T extends SequenceElement> - Class in org.deeplearning4j.models.embeddings.learning.impl.elements
-
Skip-Gram implementation for dl4j SequenceVectors
- SkipGram() - Constructor for class org.deeplearning4j.models.embeddings.learning.impl.elements.SkipGram
-
Dummy construction is required for reflection
- skipGram - Variable in class org.deeplearning4j.models.embeddings.learning.impl.sequence.DBOW
-
- skipGram(int, List<VocabWord>, int, double) - Method in class org.deeplearning4j.spark.models.embeddings.word2vec.FirstIterationFunctionAdapter
-
- skipGram(Word2VecParam, int, List<VocabWord>, int, double, List<Triple<Integer, Integer, Integer>>) - Method in class org.deeplearning4j.spark.models.embeddings.word2vec.SentenceBatch
-
Deprecated.
Train via skip gram
- skipGram(int, List<VocabWord>, int, double) - Method in class org.deeplearning4j.spark.models.embeddings.word2vec.Word2VecPerformer
-
Deprecated.
Train via skip gram
- skipGram(int, List<VocabWord>, int, double) - Method in class org.deeplearning4j.spark.models.embeddings.word2vec.Word2VecPerformerVoid
-
Deprecated.
Train via skip gram
- sla - Variable in class org.deeplearning4j.spark.models.sequencevectors.SparkSequenceVectors
-
- sleep(long) - Method in class org.deeplearning4j.optimize.listeners.SleepyTrainingListener
-
- sleep(AtomicLong, long) - Method in class org.deeplearning4j.optimize.listeners.SleepyTrainingListener
-
- sleepMode - Variable in class org.deeplearning4j.optimize.listeners.SleepyTrainingListener
-
- SleepyTrainingListener - Class in org.deeplearning4j.optimize.listeners
-
This TrainingListener implementation provides a way to "sleep" during specific Neural Network training phases.
- SleepyTrainingListener() - Constructor for class org.deeplearning4j.optimize.listeners.SleepyTrainingListener
-
- SleepyTrainingListener.SleepMode - Enum in org.deeplearning4j.optimize.listeners
-
- SleepyTrainingListener.TimeMode - Enum in org.deeplearning4j.optimize.listeners
-
- slimNode(RPNode) - Static method in class org.deeplearning4j.clustering.randomprojection.RPUtils
-
Prune indices from the given node
when it's a leaf
- slope(double, double, double, double) - Method in class org.deeplearning4j.clustering.util.MathUtils
-
This returns the slope of the given points.
- sm(double, double) - Static method in class org.deeplearning4j.clustering.util.MathUtils
-
Tests if a is smaller than b.
- SMALL - Static variable in class org.deeplearning4j.clustering.util.MathUtils
-
The small deviation allowed in double comparisons.
- softwareInfo() - Method in class org.deeplearning4j.ui.stats.sbe.InitFieldsPresentDecoder
-
- softwareInfo(boolean) - Method in class org.deeplearning4j.ui.stats.sbe.InitFieldsPresentEncoder
-
- solver - Variable in class org.deeplearning4j.nn.graph.ComputationGraph
-
- solver - Variable in class org.deeplearning4j.nn.layers.BaseLayer
-
- solver - Variable in class org.deeplearning4j.nn.layers.variational.VariationalAutoencoder
-
- solver - Variable in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
-
- Solver - Class in org.deeplearning4j.optimize
-
Generic purpose solver
- Solver() - Constructor for class org.deeplearning4j.optimize.Solver
-
- Solver.Builder - Class in org.deeplearning4j.optimize
-
- sortCandidates(INDArray, INDArray, List<Integer>, String) - Static method in class org.deeplearning4j.clustering.randomprojection.RPUtils
-
Get the sorted distances given the
query vector, input data, given the list of possible search candidates
- sourceGraph - Variable in class org.deeplearning4j.models.sequencevectors.graph.walkers.impl.NearestVertexWalker.Builder
-
- sourceGraph - Variable in class org.deeplearning4j.models.sequencevectors.graph.walkers.impl.NearestVertexWalker
-
- sourceGraph - Variable in class org.deeplearning4j.models.sequencevectors.graph.walkers.impl.RandomWalker.Builder
-
- sourceGraph - Variable in class org.deeplearning4j.models.sequencevectors.graph.walkers.impl.RandomWalker
-
- sourceGraph - Variable in class org.deeplearning4j.models.sequencevectors.transformers.impl.GraphTransformer.Builder
-
- sourceGraph - Variable in class org.deeplearning4j.models.sequencevectors.transformers.impl.GraphTransformer
-
- SpaceToBatch - Class in org.deeplearning4j.nn.layers.convolution
-
Space to batch utility layer for convolutional input types.
- SpaceToBatch(NeuralNetConfiguration) - Constructor for class org.deeplearning4j.nn.layers.convolution.SpaceToBatch
-
- SpaceToBatch(NeuralNetConfiguration, INDArray) - Constructor for class org.deeplearning4j.nn.layers.convolution.SpaceToBatch
-
- SpaceToBatchLayer - Class in org.deeplearning4j.nn.conf.layers
-
Space to batch utility layer configuration for convolutional input types.
- SpaceToBatchLayer(SpaceToBatchLayer.Builder) - Constructor for class org.deeplearning4j.nn.conf.layers.SpaceToBatchLayer
-
- SpaceToBatchLayer.Builder<T extends SpaceToBatchLayer.Builder<T>> - Class in org.deeplearning4j.nn.conf.layers
-
- SpaceToDepth - Class in org.deeplearning4j.nn.layers.convolution
-
Space to channels utility layer for convolutional input types.
- SpaceToDepth(NeuralNetConfiguration) - Constructor for class org.deeplearning4j.nn.layers.convolution.SpaceToDepth
-
- SpaceToDepth(NeuralNetConfiguration, INDArray) - Constructor for class org.deeplearning4j.nn.layers.convolution.SpaceToDepth
-
- SpaceToDepthLayer - Class in org.deeplearning4j.nn.conf.layers
-
Space to channels utility layer configuration for convolutional input types.
- SpaceToDepthLayer(SpaceToDepthLayer.Builder) - Constructor for class org.deeplearning4j.nn.conf.layers.SpaceToDepthLayer
-
- SpaceToDepthLayer.Builder<T extends SpaceToDepthLayer.Builder<T>> - Class in org.deeplearning4j.nn.conf.layers
-
- SpaceToDepthLayer.DataFormat - Enum in org.deeplearning4j.nn.conf.layers
-
- SparkADSI - Class in org.deeplearning4j.spark.iterator
-
Spark version of AsyncDataSetIterator, made separate to propagate Spark TaskContext to new background thread, for Spark block locks compatibility
- SparkADSI() - Constructor for class org.deeplearning4j.spark.iterator.SparkADSI
-
- SparkADSI(DataSetIterator) - Constructor for class org.deeplearning4j.spark.iterator.SparkADSI
-
- SparkADSI(DataSetIterator, int, BlockingQueue<DataSet>) - Constructor for class org.deeplearning4j.spark.iterator.SparkADSI
-
- SparkADSI(DataSetIterator, int) - Constructor for class org.deeplearning4j.spark.iterator.SparkADSI
-
- SparkADSI(DataSetIterator, int, boolean) - Constructor for class org.deeplearning4j.spark.iterator.SparkADSI
-
- SparkADSI(DataSetIterator, int, boolean, Integer) - Constructor for class org.deeplearning4j.spark.iterator.SparkADSI
-
- SparkADSI(DataSetIterator, int, boolean, DataSetCallback) - Constructor for class org.deeplearning4j.spark.iterator.SparkADSI
-
- SparkADSI(DataSetIterator, int, BlockingQueue<DataSet>, boolean) - Constructor for class org.deeplearning4j.spark.iterator.SparkADSI
-
- SparkADSI(DataSetIterator, int, BlockingQueue<DataSet>, boolean, DataSetCallback) - Constructor for class org.deeplearning4j.spark.iterator.SparkADSI
-
- SparkADSI(DataSetIterator, int, BlockingQueue<DataSet>, boolean, DataSetCallback, Integer) - Constructor for class org.deeplearning4j.spark.iterator.SparkADSI
-
- SparkADSI.SparkPrefetchThread - Class in org.deeplearning4j.spark.iterator
-
- SparkAMDSI - Class in org.deeplearning4j.spark.iterator
-
Spark version of AsyncMultiDataSetIterator, made separate to propagate Spark TaskContext to new background thread, for Spark block locks compatibility
- SparkAMDSI() - Constructor for class org.deeplearning4j.spark.iterator.SparkAMDSI
-
- SparkAMDSI(MultiDataSetIterator) - Constructor for class org.deeplearning4j.spark.iterator.SparkAMDSI
-
- SparkAMDSI(MultiDataSetIterator, int, BlockingQueue<MultiDataSet>) - Constructor for class org.deeplearning4j.spark.iterator.SparkAMDSI
-
- SparkAMDSI(MultiDataSetIterator, int) - Constructor for class org.deeplearning4j.spark.iterator.SparkAMDSI
-
- SparkAMDSI(MultiDataSetIterator, int, boolean) - Constructor for class org.deeplearning4j.spark.iterator.SparkAMDSI
-
- SparkAMDSI(MultiDataSetIterator, int, boolean, Integer) - Constructor for class org.deeplearning4j.spark.iterator.SparkAMDSI
-
- SparkAMDSI(MultiDataSetIterator, int, boolean, DataSetCallback) - Constructor for class org.deeplearning4j.spark.iterator.SparkAMDSI
-
- SparkAMDSI(MultiDataSetIterator, int, BlockingQueue<MultiDataSet>, boolean) - Constructor for class org.deeplearning4j.spark.iterator.SparkAMDSI
-
- SparkAMDSI(MultiDataSetIterator, int, BlockingQueue<MultiDataSet>, boolean, DataSetCallback) - Constructor for class org.deeplearning4j.spark.iterator.SparkAMDSI
-
- SparkAMDSI(MultiDataSetIterator, int, BlockingQueue<MultiDataSet>, boolean, DataSetCallback, Integer) - Constructor for class org.deeplearning4j.spark.iterator.SparkAMDSI
-
- SparkAMDSI.SparkPrefetchThread - Class in org.deeplearning4j.spark.iterator
-
- sparkAwsRegion - Variable in class org.deeplearning4j.aws.emr.SparkEMRClient.Builder
-
- sparkAwsRegion - Variable in class org.deeplearning4j.aws.emr.SparkEMRClient
-
- SparkCBOW - Class in org.deeplearning4j.spark.models.sequencevectors.learning.elements
-
- SparkCBOW() - Constructor for class org.deeplearning4j.spark.models.sequencevectors.learning.elements.SparkCBOW
-
- sparkClusterName - Variable in class org.deeplearning4j.aws.emr.SparkEMRClient.Builder
-
- sparkClusterName - Variable in class org.deeplearning4j.aws.emr.SparkEMRClient
-
- SparkComputationGraph - Class in org.deeplearning4j.spark.impl.graph
-
Main class for training ComputationGraph networks using Spark
- SparkComputationGraph(SparkContext, ComputationGraph, TrainingMaster) - Constructor for class org.deeplearning4j.spark.impl.graph.SparkComputationGraph
-
Instantiate a ComputationGraph instance with the given context and network.
- SparkComputationGraph(JavaSparkContext, ComputationGraph, TrainingMaster) - Constructor for class org.deeplearning4j.spark.impl.graph.SparkComputationGraph
-
- SparkComputationGraph(SparkContext, ComputationGraphConfiguration, TrainingMaster) - Constructor for class org.deeplearning4j.spark.impl.graph.SparkComputationGraph
-
- SparkComputationGraph(JavaSparkContext, ComputationGraphConfiguration, TrainingMaster) - Constructor for class org.deeplearning4j.spark.impl.graph.SparkComputationGraph
-
- SparkDataSetLossCalculator - Class in org.deeplearning4j.spark.earlystopping
-
Score calculator to calculate the total loss for the
MultiLayerNetwork on that data set (data set
as a
JavaRDD), using Spark.
- SparkDataSetLossCalculator(JavaRDD<DataSet>, boolean, SparkContext) - Constructor for class org.deeplearning4j.spark.earlystopping.SparkDataSetLossCalculator
-
Calculate the score (loss function value) on a given data set (usually a test set)
- SparkDataValidation - Class in org.deeplearning4j.spark.util.data
-
Utilities for validating DataSets and MultiDataSets saved (usually) in a HDFS directory.
- SparkDBOW - Class in org.deeplearning4j.spark.models.sequencevectors.learning.sequence
-
Spark implementation for PV-DBOW training algorithm
- SparkDBOW() - Constructor for class org.deeplearning4j.spark.models.sequencevectors.learning.sequence.SparkDBOW
-
- SparkDl4jMultiLayer - Class in org.deeplearning4j.spark.impl.multilayer
-
Master class for spark
- SparkDl4jMultiLayer(SparkContext, MultiLayerNetwork, TrainingMaster<?, ?>) - Constructor for class org.deeplearning4j.spark.impl.multilayer.SparkDl4jMultiLayer
-
Instantiate a multi layer spark instance
with the given context and network.
- SparkDl4jMultiLayer(SparkContext, MultiLayerConfiguration, TrainingMaster<?, ?>) - Constructor for class org.deeplearning4j.spark.impl.multilayer.SparkDl4jMultiLayer
-
Training constructor.
- SparkDl4jMultiLayer(JavaSparkContext, MultiLayerConfiguration, TrainingMaster<?, ?>) - Constructor for class org.deeplearning4j.spark.impl.multilayer.SparkDl4jMultiLayer
-
Training constructor.
- SparkDl4jMultiLayer(JavaSparkContext, MultiLayerNetwork, TrainingMaster<?, ?>) - Constructor for class org.deeplearning4j.spark.impl.multilayer.SparkDl4jMultiLayer
-
- SparkDM - Class in org.deeplearning4j.spark.models.sequencevectors.learning.sequence
-
Spark implementation for PV-DM training algorithm
- SparkDM() - Constructor for class org.deeplearning4j.spark.models.sequencevectors.learning.sequence.SparkDM
-
- SparkEarlyStoppingGraphTrainer - Class in org.deeplearning4j.spark.earlystopping
-
Class for conducting early stopping training via Spark on a ComputationGraph
- SparkEarlyStoppingGraphTrainer(SparkContext, TrainingMaster, EarlyStoppingConfiguration<ComputationGraph>, ComputationGraph, JavaRDD<MultiDataSet>, int, int) - Constructor for class org.deeplearning4j.spark.earlystopping.SparkEarlyStoppingGraphTrainer
-
- SparkEarlyStoppingGraphTrainer(JavaSparkContext, TrainingMaster, EarlyStoppingConfiguration<ComputationGraph>, ComputationGraph, JavaRDD<MultiDataSet>, int, int) - Constructor for class org.deeplearning4j.spark.earlystopping.SparkEarlyStoppingGraphTrainer
-
- SparkEarlyStoppingGraphTrainer(SparkContext, TrainingMaster, EarlyStoppingConfiguration<ComputationGraph>, ComputationGraph, JavaRDD<MultiDataSet>) - Constructor for class org.deeplearning4j.spark.earlystopping.SparkEarlyStoppingGraphTrainer
-
- SparkEarlyStoppingGraphTrainer(JavaSparkContext, TrainingMaster, EarlyStoppingConfiguration<ComputationGraph>, ComputationGraph, JavaRDD<MultiDataSet>) - Constructor for class org.deeplearning4j.spark.earlystopping.SparkEarlyStoppingGraphTrainer
-
- SparkEarlyStoppingGraphTrainer(JavaSparkContext, TrainingMaster, EarlyStoppingConfiguration<ComputationGraph>, ComputationGraph, JavaRDD<MultiDataSet>, EarlyStoppingListener<ComputationGraph>) - Constructor for class org.deeplearning4j.spark.earlystopping.SparkEarlyStoppingGraphTrainer
-
- SparkEarlyStoppingTrainer - Class in org.deeplearning4j.spark.earlystopping
-
- SparkEarlyStoppingTrainer(SparkContext, TrainingMaster, EarlyStoppingConfiguration<MultiLayerNetwork>, MultiLayerNetwork, JavaRDD<DataSet>) - Constructor for class org.deeplearning4j.spark.earlystopping.SparkEarlyStoppingTrainer
-
- SparkEarlyStoppingTrainer(JavaSparkContext, TrainingMaster, EarlyStoppingConfiguration<MultiLayerNetwork>, MultiLayerNetwork, JavaRDD<DataSet>) - Constructor for class org.deeplearning4j.spark.earlystopping.SparkEarlyStoppingTrainer
-
- SparkEarlyStoppingTrainer(SparkContext, TrainingMaster, EarlyStoppingConfiguration<MultiLayerNetwork>, MultiLayerNetwork, JavaRDD<DataSet>, EarlyStoppingListener<MultiLayerNetwork>) - Constructor for class org.deeplearning4j.spark.earlystopping.SparkEarlyStoppingTrainer
-
- SparkEarlyStoppingTrainer(JavaSparkContext, TrainingMaster, EarlyStoppingConfiguration<MultiLayerNetwork>, MultiLayerNetwork, JavaRDD<DataSet>, EarlyStoppingListener<MultiLayerNetwork>) - Constructor for class org.deeplearning4j.spark.earlystopping.SparkEarlyStoppingTrainer
-
- SparkElementsLearningAlgorithm - Interface in org.deeplearning4j.spark.models.sequencevectors.learning
-
Identification layer for Spark-ready implementations of LearningAlgorithms
- SparkEMRClient - Class in org.deeplearning4j.aws.emr
-
Configuration for a Spark EMR cluster
- SparkEMRClient() - Constructor for class org.deeplearning4j.aws.emr.SparkEMRClient
-
- SparkEMRClient.Builder - Class in org.deeplearning4j.aws.emr
-
- sparkEmrClientBuilder - Variable in class org.deeplearning4j.aws.emr.SparkEMRClient.Builder
-
- sparkEmrClientBuilder - Variable in class org.deeplearning4j.aws.emr.SparkEMRClient
-
- sparkEmrConfigs - Variable in class org.deeplearning4j.aws.emr.SparkEMRClient.Builder
-
- sparkEmrConfigs - Variable in class org.deeplearning4j.aws.emr.SparkEMRClient
-
- sparkEmrRelease - Variable in class org.deeplearning4j.aws.emr.SparkEMRClient.Builder
-
- sparkEmrRelease - Variable in class org.deeplearning4j.aws.emr.SparkEMRClient
-
- sparkEmrServiceRole - Variable in class org.deeplearning4j.aws.emr.SparkEMRClient.Builder
-
- sparkEmrServiceRole - Variable in class org.deeplearning4j.aws.emr.SparkEMRClient
-
- sparkInstanceBidPrice - Variable in class org.deeplearning4j.aws.emr.SparkEMRClient.Builder
-
- sparkInstanceBidPrice - Variable in class org.deeplearning4j.aws.emr.SparkEMRClient
-
- sparkInstanceCount - Variable in class org.deeplearning4j.aws.emr.SparkEMRClient.Builder
-
- sparkInstanceCount - Variable in class org.deeplearning4j.aws.emr.SparkEMRClient
-
- sparkInstanceRole - Variable in class org.deeplearning4j.aws.emr.SparkEMRClient.Builder
-
- sparkInstanceRole - Variable in class org.deeplearning4j.aws.emr.SparkEMRClient
-
- sparkInstanceType - Variable in class org.deeplearning4j.aws.emr.SparkEMRClient.Builder
-
- sparkInstanceType - Variable in class org.deeplearning4j.aws.emr.SparkEMRClient
-
- sparkJobFlowInstancesConfig - Variable in class org.deeplearning4j.aws.emr.SparkEMRClient.Builder
-
- sparkJobFlowInstancesConfig - Variable in class org.deeplearning4j.aws.emr.SparkEMRClient
-
- SparkListenable - Class in org.deeplearning4j.spark.impl
-
Created by huitseeker on 2/15/17.
- SparkListenable() - Constructor for class org.deeplearning4j.spark.impl.SparkListenable
-
- SparkLossCalculatorComputationGraph - Class in org.deeplearning4j.spark.earlystopping
-
Score calculator to calculate the total loss for the
ComputationGraph on that data set (data set
as a
JavaRDD), using Spark.
Typically used to calculate the loss on a test set.
Note: to test a ComputationGraph on a
DataSet use
DataSetToMultiDataSetFn
- SparkLossCalculatorComputationGraph(JavaRDD<MultiDataSet>, boolean, SparkContext) - Constructor for class org.deeplearning4j.spark.earlystopping.SparkLossCalculatorComputationGraph
-
Calculate the score (loss function value) on a given data set (usually a test set)
- SparkModelExporter<T extends SequenceElement> - Interface in org.deeplearning4j.spark.models.sequencevectors.export
-
This interface describes
- sparkMonitor() - Method in class org.deeplearning4j.aws.emr.SparkEMRClient
-
Monitor the cluster and terminates when it times out
- SparkParagraphVectors - Class in org.deeplearning4j.spark.models.paragraphvectors
-
- SparkParagraphVectors() - Constructor for class org.deeplearning4j.spark.models.paragraphvectors.SparkParagraphVectors
-
- SparkPrefetchThread(BlockingQueue<DataSet>, DataSetIterator, DataSet, MemoryWorkspace) - Constructor for class org.deeplearning4j.spark.iterator.SparkADSI.SparkPrefetchThread
-
- SparkPrefetchThread(BlockingQueue<MultiDataSet>, MultiDataSetIterator, MultiDataSet) - Constructor for class org.deeplearning4j.spark.iterator.SparkAMDSI.SparkPrefetchThread
-
- sparkRunJobFlowRequest - Variable in class org.deeplearning4j.aws.emr.SparkEMRClient.Builder
-
- sparkRunJobFlowRequest - Variable in class org.deeplearning4j.aws.emr.SparkEMRClient
-
- sparkS3ClientBuilder - Variable in class org.deeplearning4j.aws.emr.SparkEMRClient.Builder
-
- sparkS3ClientBuilder - Variable in class org.deeplearning4j.aws.emr.SparkEMRClient
-
- sparkS3JarFolder - Variable in class org.deeplearning4j.aws.emr.SparkEMRClient.Builder
-
- sparkS3JarFolder - Variable in class org.deeplearning4j.aws.emr.SparkEMRClient
-
- sparkS3PutObjectDecorator - Variable in class org.deeplearning4j.aws.emr.SparkEMRClient.Builder
-
- sparkS3PutObjectDecorator - Variable in class org.deeplearning4j.aws.emr.SparkEMRClient
-
- sparkSecurityGroupIds - Variable in class org.deeplearning4j.aws.emr.SparkEMRClient.Builder
-
- sparkSecurityGroupIds - Variable in class org.deeplearning4j.aws.emr.SparkEMRClient
-
- SparkSequenceLearningAlgorithm - Interface in org.deeplearning4j.spark.models.sequencevectors.learning
-
Identification layer for Spark-ready implementations of LearningAlgorithms
- SparkSequenceVectors<T extends SequenceElement> - Class in org.deeplearning4j.spark.models.sequencevectors
-
Generic SequenceVectors implementation for dl4j-spark-nlp
- SparkSequenceVectors() - Constructor for class org.deeplearning4j.spark.models.sequencevectors.SparkSequenceVectors
-
- SparkSequenceVectors(VectorsConfiguration) - Constructor for class org.deeplearning4j.spark.models.sequencevectors.SparkSequenceVectors
-
- SparkSequenceVectors.Builder<T extends SequenceElement> - Class in org.deeplearning4j.spark.models.sequencevectors
-
- SparkSkipGram - Class in org.deeplearning4j.spark.models.sequencevectors.learning.elements
-
- SparkSkipGram() - Constructor for class org.deeplearning4j.spark.models.sequencevectors.learning.elements.SparkSkipGram
-
- SparkSourceDummyReader - Class in org.deeplearning4j.spark.datavec.iterator
-
- SparkSourceDummyReader(int) - Constructor for class org.deeplearning4j.spark.datavec.iterator.SparkSourceDummyReader
-
- SparkSourceDummySeqReader - Class in org.deeplearning4j.spark.datavec.iterator
-
- SparkSourceDummySeqReader(int) - Constructor for class org.deeplearning4j.spark.datavec.iterator.SparkSourceDummySeqReader
-
- sparkSubmitConfs - Variable in class org.deeplearning4j.aws.emr.SparkEMRClient.Builder
-
- sparkSubmitConfs - Variable in class org.deeplearning4j.aws.emr.SparkEMRClient
-
- sparkSubmitJobWithMain(String[], String, File) - Method in class org.deeplearning4j.aws.emr.SparkEMRClient
-
Submit a Spark Job with a specified main class
- sparkSubNetid - Variable in class org.deeplearning4j.aws.emr.SparkEMRClient.Builder
-
- sparkSubnetId - Variable in class org.deeplearning4j.aws.emr.SparkEMRClient
-
- sparkTimeoutDurationMinutes - Variable in class org.deeplearning4j.aws.emr.SparkEMRClient.Builder
-
- sparkTimeOutDurationMinutes(int) - Method in class org.deeplearning4j.aws.emr.SparkEMRClient.Builder
-
The timeout duration for this Spark EMR cluster, in minutes
- sparkTimeoutDurationMinutes - Variable in class org.deeplearning4j.aws.emr.SparkEMRClient
-
- SparkTrainingStats - Interface in org.deeplearning4j.spark.api.stats
-
SparkTrainingStats is an interface that is used for accessing training statistics, for multiple
TrainingMaster
implementations.
- SparkUtils - Class in org.deeplearning4j.spark.util
-
Various utilities for Spark
- SparkWord2Vec - Class in org.deeplearning4j.spark.models.word2vec
-
- SparkWord2Vec() - Constructor for class org.deeplearning4j.spark.models.word2vec.SparkWord2Vec
-
- SparkWord2Vec(VoidConfiguration, VectorsConfiguration) - Constructor for class org.deeplearning4j.spark.models.word2vec.SparkWord2Vec
-
- SparkWord2Vec.Builder - Class in org.deeplearning4j.spark.models.word2vec
-
- sparseCounter - Variable in class org.deeplearning4j.spark.parameterserver.networking.SilentTrainingDriver
-
- sparsity(double) - Method in class org.deeplearning4j.nn.conf.layers.AutoEncoder.Builder
-
- sparsity - Variable in class org.deeplearning4j.nn.conf.layers.AutoEncoder
-
- SpatialDropout - Class in org.deeplearning4j.nn.conf.dropout
-
Spatial dropout: can only be applied to 4D (convolutional) activations.
- SpatialDropout(double) - Constructor for class org.deeplearning4j.nn.conf.dropout.SpatialDropout
-
- SpatialDropout(ISchedule) - Constructor for class org.deeplearning4j.nn.conf.dropout.SpatialDropout
-
- SpatialDropout(double, ISchedule) - Constructor for class org.deeplearning4j.nn.conf.dropout.SpatialDropout
-
- special - Variable in class org.deeplearning4j.models.sequencevectors.sequence.SequenceElement
-
- spectrum - Variable in class org.deeplearning4j.models.sequencevectors.graph.walkers.impl.PopularityWalker.Builder
-
- spectrum - Variable in class org.deeplearning4j.models.sequencevectors.graph.walkers.impl.PopularityWalker
-
- split - Variable in class com.atilika.kuromoji.TokenizerBase.Builder
-
- split - Variable in class org.ansj.domain.PersonNatureAttr
-
- split(T) - Method in class org.deeplearning4j.datasets.iterator.file.BaseFileIterator
-
- split(DataSet) - Method in class org.deeplearning4j.datasets.iterator.file.FileDataSetIterator
-
- split(MultiDataSet) - Method in class org.deeplearning4j.datasets.iterator.file.FileMultiDataSetIterator
-
- splitClusters(ClusterSet, ClusterSetInfo, List<Cluster>, double, ExecutorService) - Static method in class org.deeplearning4j.clustering.cluster.ClusterUtils
-
- splitClusters(ClusterSet, ClusterSetInfo, List<Cluster>, ExecutorService) - Static method in class org.deeplearning4j.clustering.cluster.ClusterUtils
-
- splitClustersWhereAverageDistanceFromCenterGreaterThan(ClusterSet, ClusterSetInfo, double, ExecutorService) - Static method in class org.deeplearning4j.clustering.cluster.ClusterUtils
-
- splitClustersWhereMaximumDistanceFromCenterGreaterThan(ClusterSet, ClusterSetInfo, double, ExecutorService) - Static method in class org.deeplearning4j.clustering.cluster.ClusterUtils
-
- SplitDataSetExamplesPairFlatMapFunction - Class in org.deeplearning4j.spark.data.shuffle
-
A PairFlatMapFunction that splits each example in a DataSet object into its own DataSet.
- SplitDataSetExamplesPairFlatMapFunction(int) - Constructor for class org.deeplearning4j.spark.data.shuffle.SplitDataSetExamplesPairFlatMapFunction
-
- SplitDataSetsFunction - Class in org.deeplearning4j.spark.data
-
Take an existing DataSet object, and split it into multiple DataSet objects with one example in each
Usage:
- SplitDataSetsFunction() - Constructor for class org.deeplearning4j.spark.data.SplitDataSetsFunction
-
- splitMostPopulatedClusters(ClusterSet, ClusterSetInfo, int, ExecutorService) - Static method in class org.deeplearning4j.clustering.cluster.ClusterUtils
-
- splitMostSpreadOutClusters(ClusterSet, ClusterSetInfo, int, ExecutorService) - Static method in class org.deeplearning4j.clustering.cluster.ClusterUtils
-
- SplitPartitionsFunction<T> - Class in org.deeplearning4j.spark.impl.common
-
SplitPartitionsFunction is used to split a RDD (using AbstractJavaRDDLike.mapPartitionsWithIndex(Function2, boolean)
via filtering.
It is similar in design to JavaRDD.randomSplit(double[]) however it is less prone to
producing imbalanced splits that that method.
- SplitPartitionsFunction() - Constructor for class org.deeplearning4j.spark.impl.common.SplitPartitionsFunction
-
- SplitPartitionsFunction2<T,U> - Class in org.deeplearning4j.spark.impl.common
-
- SplitPartitionsFunction2() - Constructor for class org.deeplearning4j.spark.impl.common.SplitPartitionsFunction2
-
- splitStr - Variable in class org.ansj.app.crf.Config
-
- SplitWord - Class in org.ansj.app.crf
-
分词
- SplitWord(Model) - Constructor for class org.ansj.app.crf.SplitWord
-
- spread - Variable in class org.deeplearning4j.models.sequencevectors.graph.walkers.impl.PopularityWalker.Builder
-
- spread - Variable in class org.deeplearning4j.models.sequencevectors.graph.walkers.impl.PopularityWalker
-
- SpreadSpectrum - Enum in org.deeplearning4j.models.sequencevectors.graph.enums
-
This enum describes nodes selection for PopularityWalker.
- SpTree - Class in org.deeplearning4j.clustering.sptree
-
- SpTree(SpTree, INDArray, INDArray, INDArray, Set<INDArray>, String) - Constructor for class org.deeplearning4j.clustering.sptree.SpTree
-
- SpTree(INDArray, Set<INDArray>, String) - Constructor for class org.deeplearning4j.clustering.sptree.SpTree
-
- SpTree(SpTree, INDArray, INDArray, INDArray, Set<INDArray>) - Constructor for class org.deeplearning4j.clustering.sptree.SpTree
-
- SpTree(INDArray, Set<INDArray>) - Constructor for class org.deeplearning4j.clustering.sptree.SpTree
-
- SpTree(INDArray) - Constructor for class org.deeplearning4j.clustering.sptree.SpTree
-
- squaredLoss(double[], double[], double, double) - Static method in class org.deeplearning4j.clustering.util.MathUtils
-
This will return the squared loss of the given
points
- SqueezeNet - Class in org.deeplearning4j.zoo.model
-
U-Net
An implementation of SqueezeNet.
- ssError(double[], double[]) - Static method in class org.deeplearning4j.clustering.util.MathUtils
-
How much of the variance is NOT explained by the regression
- ssReg(double[], double[]) - Static method in class org.deeplearning4j.clustering.util.MathUtils
-
How much of the variance is explained by the regression
- ssTotal(double[], double[]) - Static method in class org.deeplearning4j.clustering.util.MathUtils
-
Total variance in target attribute
- stackSize - Variable in class org.deeplearning4j.nn.conf.graph.UnstackVertex
-
- StackVertex - Class in org.deeplearning4j.nn.conf.graph
-
StackVertex allows for stacking of inputs so that they may be forwarded through
a network.
- StackVertex() - Constructor for class org.deeplearning4j.nn.conf.graph.StackVertex
-
- StackVertex - Class in org.deeplearning4j.nn.graph.vertex.impl
-
StackVertex allows for stacking of inputs so that they may be forwarded through
a network.
- StackVertex(ComputationGraph, String, int) - Constructor for class org.deeplearning4j.nn.graph.vertex.impl.StackVertex
-
- StackVertex(ComputationGraph, String, int, VertexIndices[], VertexIndices[]) - Constructor for class org.deeplearning4j.nn.graph.vertex.impl.StackVertex
-
- standardMemory(long, long) - Method in class org.deeplearning4j.nn.conf.memory.LayerMemoryReport.Builder
-
Report the standard memory
- start() - Method in interface org.deeplearning4j.parallelism.trainer.Trainer
-
Start this trainer
- start() - Method in class org.deeplearning4j.streaming.kafka.NDArrayConsumer
-
Start the consumer
- start() - Method in class org.deeplearning4j.streaming.kafka.NDArrayPublisher
-
Start the publisher
- startTime - Variable in class org.deeplearning4j.spark.stats.BaseEventStats
-
- StartTimeComparator() - Constructor for class org.deeplearning4j.spark.stats.StatsUtils.StartTimeComparator
-
- startTraining(SilentUpdatesMessage) - Method in class org.deeplearning4j.spark.parameterserver.networking.SilentTrainingDriver
-
- state - Variable in class org.deeplearning4j.optimize.solvers.accumulation.FancyBlockingQueue
-
- state - Variable in class org.deeplearning4j.spark.parameterserver.iterators.VirtualIterator
-
- state - Variable in class org.deeplearning4j.spark.parameterserver.util.BlockingObserver
-
- STATE_KEY_PREV_ACTIVATION - Static variable in class org.deeplearning4j.nn.layers.recurrent.GravesLSTM
-
- STATE_KEY_PREV_ACTIVATION - Static variable in class org.deeplearning4j.nn.layers.recurrent.LSTM
-
- STATE_KEY_PREV_ACTIVATION - Static variable in class org.deeplearning4j.nn.layers.recurrent.SimpleRnn
-
- STATE_KEY_PREV_MEMCELL - Static variable in class org.deeplearning4j.nn.layers.recurrent.GravesLSTM
-
- STATE_KEY_PREV_MEMCELL - Static variable in class org.deeplearning4j.nn.layers.recurrent.LSTM
-
- stateMap - Variable in class org.deeplearning4j.nn.layers.recurrent.BaseRecurrentLayer
-
stateMap stores the INDArrays needed to do rnnTimeStep() forward pass.
- states - Variable in class org.deeplearning4j.datasets.iterator.parallel.BaseParallelDataSetIterator
-
- staticInfo - Variable in class org.deeplearning4j.ui.storage.BaseCollectionStatsStorage
-
- StaticInfoDecoder - Class in org.deeplearning4j.ui.stats.sbe
-
- StaticInfoDecoder() - Constructor for class org.deeplearning4j.ui.stats.sbe.StaticInfoDecoder
-
- StaticInfoDecoder.HwDeviceInfoGroupDecoder - Class in org.deeplearning4j.ui.stats.sbe
-
- StaticInfoDecoder.ModelParamNamesDecoder - Class in org.deeplearning4j.ui.stats.sbe
-
- StaticInfoDecoder.SwEnvironmentInfoDecoder - Class in org.deeplearning4j.ui.stats.sbe
-
- StaticInfoEncoder - Class in org.deeplearning4j.ui.stats.sbe
-
- StaticInfoEncoder() - Constructor for class org.deeplearning4j.ui.stats.sbe.StaticInfoEncoder
-
- StaticInfoEncoder.HwDeviceInfoGroupEncoder - Class in org.deeplearning4j.ui.stats.sbe
-
- StaticInfoEncoder.ModelParamNamesEncoder - Class in org.deeplearning4j.ui.stats.sbe
-
- StaticInfoEncoder.SwEnvironmentInfoEncoder - Class in org.deeplearning4j.ui.stats.sbe
-
- StaticPageUtil - Class in org.deeplearning4j.ui.standalone
-
Idea: Render a set of components as a single static page.
- StaticWord2Vec - Class in org.deeplearning4j.models.word2vec
-
This is special limited Word2Vec implementation, suited for serving as lookup table in concurrent multi-gpu environment
This implementation DOES NOT load all vectors onto any of gpus, instead of that it holds vectors in, optionally, compressed state in host memory.
- StaticWord2Vec.Builder - Class in org.deeplearning4j.models.word2vec
-
- stats() - Method in class org.deeplearning4j.eval.Evaluation
-
Report the classification statistics as a String
- stats(boolean) - Method in class org.deeplearning4j.eval.Evaluation
-
Method to obtain the classification report as a String
- stats(boolean, boolean) - Method in class org.deeplearning4j.eval.Evaluation
-
Method to obtain the classification report as a String
- stats() - Method in class org.deeplearning4j.eval.EvaluationBinary
-
Get a String representation of the EvaluationBinary class, using the default precision
- stats(int) - Method in class org.deeplearning4j.eval.EvaluationBinary
-
Get a String representation of the EvaluationBinary class, using the specified precision
- stats() - Method in class org.deeplearning4j.eval.EvaluationCalibration
-
- stats() - Method in interface org.deeplearning4j.eval.IEvaluation
-
- stats() - Method in class org.deeplearning4j.eval.RegressionEvaluation
-
- stats() - Method in class org.deeplearning4j.eval.ROC
-
- stats() - Method in class org.deeplearning4j.eval.ROCBinary
-
- stats(int) - Method in class org.deeplearning4j.eval.ROCBinary
-
- stats() - Method in class org.deeplearning4j.eval.ROCMultiClass
-
- stats(int) - Method in class org.deeplearning4j.eval.ROCMultiClass
-
- stats - Variable in class org.deeplearning4j.spark.impl.paramavg.BaseTrainingMaster
-
- stats - Variable in class org.deeplearning4j.spark.parameterserver.training.SharedTrainingMaster
-
- statsAsString() - Method in class org.deeplearning4j.spark.api.stats.CommonSparkTrainingStats
-
- statsAsString() - Method in interface org.deeplearning4j.spark.api.stats.SparkTrainingStats
-
Get a String representation of the stats.
- statsAsString() - Method in class org.deeplearning4j.spark.impl.paramavg.stats.ParameterAveragingTrainingMasterStats
-
- statsAsString() - Method in class org.deeplearning4j.spark.impl.paramavg.stats.ParameterAveragingTrainingWorkerStats
-
- StatsCalculationHelper - Class in org.deeplearning4j.spark.api.stats
-
- StatsCalculationHelper() - Constructor for class org.deeplearning4j.spark.api.stats.StatsCalculationHelper
-
- statsCollectionDuration() - Method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder
-
- statsCollectionDuration(int) - Method in class org.deeplearning4j.ui.stats.sbe.UpdateEncoder
-
- statsCollectionDurationId() - Static method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder
-
- statsCollectionDurationMaxValue() - Static method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder
-
- statsCollectionDurationMaxValue() - Static method in class org.deeplearning4j.ui.stats.sbe.UpdateEncoder
-
- statsCollectionDurationMetaAttribute(MetaAttribute) - Static method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder
-
- statsCollectionDurationMinValue() - Static method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder
-
- statsCollectionDurationMinValue() - Static method in class org.deeplearning4j.ui.stats.sbe.UpdateEncoder
-
- statsCollectionDurationNullValue() - Static method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder
-
- statsCollectionDurationNullValue() - Static method in class org.deeplearning4j.ui.stats.sbe.UpdateEncoder
-
- StatsInitializationConfiguration - Interface in org.deeplearning4j.ui.stats.api
-
Configuration interface for static (unchanging) information, to be reported by
StatsListener.
- StatsInitializationReport - Interface in org.deeplearning4j.ui.stats.api
-
An interface used with
StatsListener for reporting static information.
- StatsListener - Class in org.deeplearning4j.ui.stats
-
StatsListener: a general purpose listener for collecting and reporting system and model information.
- StatsListener(StatsStorageRouter) - Constructor for class org.deeplearning4j.ui.stats.StatsListener
-
Create a StatsListener with network information collected at every iteration.
- StatsListener(StatsStorageRouter, int) - Constructor for class org.deeplearning4j.ui.stats.StatsListener
-
Create a StatsListener with network information collected every n >= 1 time steps
- StatsListener(StatsStorageRouter, StatsInitializationConfiguration, StatsUpdateConfiguration, String, String) - Constructor for class org.deeplearning4j.ui.stats.StatsListener
-
- StatSource - Enum in org.deeplearning4j.ui.stats.sbe
-
- StatsReport - Interface in org.deeplearning4j.ui.stats.api
-
StatsReport: An interface for storing and serializing update information (such as scores, parameter histograms etc) for
use in the
StatsListener
- StatsStorage - Interface in org.deeplearning4j.api.storage
-
A general-purpose stats storage mechanism, for storing stats information (mainly used for iteration listeners).
- statsStorage - Variable in class org.deeplearning4j.spark.impl.paramavg.BaseTrainingMaster
-
- StatsStorageEvent - Class in org.deeplearning4j.api.storage
-
- StatsStorageEvent() - Constructor for class org.deeplearning4j.api.storage.StatsStorageEvent
-
- StatsStorageListener - Interface in org.deeplearning4j.api.storage
-
A listener interface, so that classes can be notified of changes to a
StatsStorage
implementation
- StatsStorageListener.EventType - Enum in org.deeplearning4j.api.storage
-
- StatsStorageRouter - Interface in org.deeplearning4j.api.storage
-
StatsStorageRouter is intended to route static info, metadata and updates somewhere - generally to a
StatsStorage implementation.
- StatsStorageRouterProvider - Interface in org.deeplearning4j.api.storage
-
Simple interface to provide a StatsStorageRouter.
- StatsType - Enum in org.deeplearning4j.ui.stats.api
-
Stats type, for use in
StatsListener
Note: Gradients are pre-update (i.e., raw gradients - pre-LR/momentum/rmsprop etc), Updates are post update
- StatsType - Enum in org.deeplearning4j.ui.stats.sbe
-
- StatsUpdateConfiguration - Interface in org.deeplearning4j.ui.stats.api
-
- StatsUtils - Class in org.deeplearning4j.spark.stats
-
Utility methods for Spark training stats
- StatsUtils.StartTimeComparator - Class in org.deeplearning4j.spark.stats
-
- StatType - Enum in org.deeplearning4j.ui.stats.sbe
-
- statType() - Method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder.PerParameterStatsDecoder.HistogramsDecoder
-
- statType() - Method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder.PerParameterStatsDecoder.SummaryStatDecoder
-
- statType(StatsType) - Method in class org.deeplearning4j.ui.stats.sbe.UpdateEncoder.PerParameterStatsEncoder.HistogramsEncoder
-
- statType(StatsType) - Method in class org.deeplearning4j.ui.stats.sbe.UpdateEncoder.PerParameterStatsEncoder.SummaryStatEncoder
-
- statTypeId() - Static method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder.PerParameterStatsDecoder.HistogramsDecoder
-
- statTypeId() - Static method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder.PerParameterStatsDecoder.SummaryStatDecoder
-
- statTypeMetaAttribute(MetaAttribute) - Static method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder.PerParameterStatsDecoder.HistogramsDecoder
-
- statTypeMetaAttribute(MetaAttribute) - Static method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder.PerParameterStatsDecoder.SummaryStatDecoder
-
- status - Variable in class org.ansj.app.crf.Model
-
- status(char) - Static method in class org.ansj.library.DATDictionary
-
- STATUS_UPDATE_FREQUENCY - Static variable in class org.deeplearning4j.graph.models.deepwalk.DeepWalk
-
- std - Variable in class org.deeplearning4j.nn.layers.normalization.BatchNormalization
-
- stdevActivations() - Method in class org.deeplearning4j.ui.stats.sbe.UpdateFieldsPresentDecoder
-
- stdevActivations(boolean) - Method in class org.deeplearning4j.ui.stats.sbe.UpdateFieldsPresentEncoder
-
- stdevGradients() - Method in class org.deeplearning4j.ui.stats.sbe.UpdateFieldsPresentDecoder
-
- stdevGradients(boolean) - Method in class org.deeplearning4j.ui.stats.sbe.UpdateFieldsPresentEncoder
-
- stdevParameters() - Method in class org.deeplearning4j.ui.stats.sbe.UpdateFieldsPresentDecoder
-
- stdevParameters(boolean) - Method in class org.deeplearning4j.ui.stats.sbe.UpdateFieldsPresentEncoder
-
- stdevUpdates() - Method in class org.deeplearning4j.ui.stats.sbe.UpdateFieldsPresentDecoder
-
- stdevUpdates(boolean) - Method in class org.deeplearning4j.ui.stats.sbe.UpdateFieldsPresentEncoder
-
- stem - Variable in class org.deeplearning4j.bagofwords.vectorizer.Builder
-
Deprecated.
- stem(boolean) - Method in class org.deeplearning4j.bagofwords.vectorizer.Builder
-
Deprecated.
- StemmerAnnotator - Class in org.deeplearning4j.text.annotator
-
- StemmerAnnotator() - Constructor for class org.deeplearning4j.text.annotator.StemmerAnnotator
-
- StemmingPreprocessor - Class in org.deeplearning4j.text.tokenization.tokenizer.preprocessor
-
This tokenizer preprocessor implements basic cleaning inherited from CommonPreprocessor + does english Porter stemming on tokens
PLEASE NOTE: This preprocessor is thread-safe by using synchronized method
- StemmingPreprocessor() - Constructor for class org.deeplearning4j.text.tokenization.tokenizer.preprocessor.StemmingPreprocessor
-
- step(INDArray, INDArray, double) - Method in interface org.deeplearning4j.optimize.api.StepFunction
-
Step with the given parameters
- step(INDArray, INDArray) - Method in interface org.deeplearning4j.optimize.api.StepFunction
-
Step with no parameters
- step() - Method in interface org.deeplearning4j.optimize.api.StepFunction
-
- step - Variable in class org.deeplearning4j.optimize.solvers.accumulation.FancyBlockingQueue
-
- step - Variable in class org.deeplearning4j.optimize.solvers.BaseOptimizer
-
- step(INDArray, INDArray, double) - Method in class org.deeplearning4j.optimize.stepfunctions.DefaultStepFunction
-
Does x = x + stepSize * line
- step(INDArray, INDArray) - Method in class org.deeplearning4j.optimize.stepfunctions.DefaultStepFunction
-
- step() - Method in class org.deeplearning4j.optimize.stepfunctions.DefaultStepFunction
-
- step(INDArray, INDArray, double) - Method in class org.deeplearning4j.optimize.stepfunctions.GradientStepFunction
-
- step(INDArray, INDArray) - Method in class org.deeplearning4j.optimize.stepfunctions.GradientStepFunction
-
- step() - Method in class org.deeplearning4j.optimize.stepfunctions.GradientStepFunction
-
- step(INDArray, INDArray, double) - Method in class org.deeplearning4j.optimize.stepfunctions.NegativeDefaultStepFunction
-
- step(INDArray, INDArray) - Method in class org.deeplearning4j.optimize.stepfunctions.NegativeDefaultStepFunction
-
- step() - Method in class org.deeplearning4j.optimize.stepfunctions.NegativeDefaultStepFunction
-
- step(INDArray, INDArray, double) - Method in class org.deeplearning4j.optimize.stepfunctions.NegativeGradientStepFunction
-
- step(INDArray, INDArray) - Method in class org.deeplearning4j.optimize.stepfunctions.NegativeGradientStepFunction
-
- step() - Method in class org.deeplearning4j.optimize.stepfunctions.NegativeGradientStepFunction
-
- step(INDArray, int) - Method in class org.deeplearning4j.plot.BarnesHutTsne
-
An individual iteration
- stepDelay - Variable in class org.deeplearning4j.optimize.solvers.accumulation.EncodingHandler
-
- stepDelay - Variable in class org.deeplearning4j.spark.parameterserver.conf.SharedTrainingConfiguration
-
- stepDelay - Variable in class org.deeplearning4j.spark.parameterserver.training.SharedTrainingMaster.Builder
-
- stepDelay(int) - Method in class org.deeplearning4j.spark.parameterserver.training.SharedTrainingMaster.Builder
-
Wait at least X iterations between applying threshold decay
Default value: 50
- stepDelay - Variable in class org.deeplearning4j.spark.parameterserver.training.SharedTrainingMaster
-
- stepForward() - Method in class org.deeplearning4j.datasets.iterator.parallel.BaseParallelDataSetIterator
-
- stepFunction - Variable in class org.deeplearning4j.nn.conf.NeuralNetConfiguration.Builder
-
- stepFunction(StepFunction) - Method in class org.deeplearning4j.nn.conf.NeuralNetConfiguration.Builder
-
Deprecated.
- stepFunction - Variable in class org.deeplearning4j.nn.conf.NeuralNetConfiguration
-
- StepFunction - Class in org.deeplearning4j.nn.conf.stepfunctions
-
Custom step function for line search.
- StepFunction() - Constructor for class org.deeplearning4j.nn.conf.stepfunctions.StepFunction
-
- stepFunction(StepFunction) - Method in class org.deeplearning4j.nn.transferlearning.FineTuneConfiguration.Builder
-
- stepFunction - Variable in class org.deeplearning4j.nn.transferlearning.FineTuneConfiguration
-
- StepFunction - Interface in org.deeplearning4j.optimize.api
-
Custom step function for line search
- stepFunction - Variable in class org.deeplearning4j.optimize.solvers.BaseOptimizer
-
- stepFunction - Variable in class org.deeplearning4j.spark.parameterserver.networking.SilentTrainingDriver
-
- StepFunctions - Class in org.deeplearning4j.optimize.stepfunctions
-
- stepMax - Variable in class org.deeplearning4j.optimize.solvers.BaseOptimizer
-
- stepTrigger - Variable in class org.deeplearning4j.optimize.solvers.accumulation.EncodingHandler
-
- stepTrigger - Variable in class org.deeplearning4j.spark.parameterserver.conf.SharedTrainingConfiguration
-
- stepTrigger - Variable in class org.deeplearning4j.spark.parameterserver.training.SharedTrainingMaster.Builder
-
- stepTrigger(double) - Method in class org.deeplearning4j.spark.parameterserver.training.SharedTrainingMaster.Builder
-
Target sparsity/dense level, when threshold step will happen.
- stepTrigger - Variable in class org.deeplearning4j.spark.parameterserver.training.SharedTrainingMaster
-
- StochasticGradientDescent - Class in org.deeplearning4j.optimize.solvers
-
Stochastic Gradient Descent
Standard fix step size
No line search
- StochasticGradientDescent(NeuralNetConfiguration, StepFunction, Collection<TrainingListener>, Model) - Constructor for class org.deeplearning4j.optimize.solvers.StochasticGradientDescent
-
- StochasticGradientDescent(NeuralNetConfiguration, StepFunction, Collection<TrainingListener>, Collection<TerminationCondition>, Model) - Constructor for class org.deeplearning4j.optimize.solvers.StochasticGradientDescent
-
- STOP - Variable in class org.deeplearning4j.models.sequencevectors.SequenceVectors.Builder
-
- stop() - Method in class org.deeplearning4j.nearestneighbor.server.NearestNeighborsServer
-
Stop the server
- stop() - Method in class org.deeplearning4j.ui.api.UIServer
-
Stop/shut down the UI server.
- stop() - Method in class org.deeplearning4j.ui.play.PlayUIServer
-
- stopFit - Variable in class org.deeplearning4j.parallelism.ParallelWrapper
-
- stopFit() - Method in class org.deeplearning4j.parallelism.ParallelWrapper
-
Will stop a fit operation from continuing to iterate.
- StopLibrary - Class in org.ansj.library
-
- StopLibrary() - Constructor for class org.ansj.library.StopLibrary
-
- stopLyingIteration(int) - Method in class org.deeplearning4j.plot.BarnesHutTsne.Builder
-
- stopLyingIteration - Variable in class org.deeplearning4j.plot.BarnesHutTsne
-
- stopLyingIteration - Variable in class org.deeplearning4j.plot.Tsne.Builder
-
- stopLyingIteration(int) - Method in class org.deeplearning4j.plot.Tsne.Builder
-
- stopLyingIteration - Variable in class org.deeplearning4j.plot.Tsne
-
- stopPolling() - Method in class org.deeplearning4j.perf.listener.SystemPolling
-
Shut down the background polling
- StopRecognition - Class in org.ansj.recognition.impl
-
对结果增加过滤,支持词性过滤,和词语过滤.
- StopRecognition() - Constructor for class org.ansj.recognition.impl.StopRecognition
-
- stopWords - Variable in class org.deeplearning4j.bagofwords.vectorizer.BagOfWordsVectorizer.Builder
-
- stopWords - Variable in class org.deeplearning4j.bagofwords.vectorizer.BaseTextVectorizer
-
- stopWords - Variable in class org.deeplearning4j.bagofwords.vectorizer.Builder
-
Deprecated.
- stopWords(List<String>) - Method in class org.deeplearning4j.bagofwords.vectorizer.Builder
-
Deprecated.
- stopWords - Variable in class org.deeplearning4j.bagofwords.vectorizer.TfidfVectorizer.Builder
-
- stopWords - Variable in class org.deeplearning4j.models.embeddings.wordvectors.WordVectorsImpl
-
- stopWords(List<String>) - Method in class org.deeplearning4j.models.glove.Glove.Builder
-
- stopWords(Collection<VocabWord>) - Method in class org.deeplearning4j.models.glove.Glove.Builder
-
- stopWords(List<String>) - Method in class org.deeplearning4j.models.node2vec.Node2Vec.Builder
-
Deprecated.
- stopWords(Collection<V>) - Method in class org.deeplearning4j.models.node2vec.Node2Vec.Builder
-
Deprecated.
- stopWords(List<String>) - Method in class org.deeplearning4j.models.paragraphvectors.ParagraphVectors.Builder
-
This method defines stop words that should be ignored during training
- stopWords(Collection<VocabWord>) - Method in class org.deeplearning4j.models.paragraphvectors.ParagraphVectors.Builder
-
This method defines stop words that should be ignored during training
- stopWords - Variable in class org.deeplearning4j.models.sequencevectors.SequenceVectors.Builder
-
- stopWords(List<String>) - Method in class org.deeplearning4j.models.sequencevectors.SequenceVectors.Builder
-
You can provide collection of objects to be ignored, and excluded out of model
Please note: Object labels and hashCode will be used for filtering
- stopWords(Collection<T>) - Method in class org.deeplearning4j.models.sequencevectors.SequenceVectors.Builder
-
You can provide collection of objects to be ignored, and excluded out of model
Please note: Object labels and hashCode will be used for filtering
- stopWords(List<String>) - Method in class org.deeplearning4j.models.word2vec.Word2Vec.Builder
-
This method defines stop words that should be ignored during training
- stopWords(Collection<VocabWord>) - Method in class org.deeplearning4j.models.word2vec.Word2Vec.Builder
-
This method defines stop words that should be ignored during training
- stopWords - Variable in class org.deeplearning4j.spark.models.embeddings.word2vec.Word2Vec.Builder
-
- stopWords(List<String>) - Method in class org.deeplearning4j.spark.models.embeddings.word2vec.Word2Vec.Builder
-
This method defines list of stop-words, that are to be ignored during vocab building and training
- StopWords - Class in org.deeplearning4j.text.stopwords
-
Loads stop words from the class path
- storage - Variable in class org.deeplearning4j.optimize.solvers.accumulation.BasicGradientsAccumulator
-
- storage - Variable in class org.deeplearning4j.spark.parameterserver.networking.SilentTrainingDriver
-
- storageId - Variable in class org.deeplearning4j.models.sequencevectors.sequence.SequenceElement
-
- storageLevel - Variable in class org.deeplearning4j.spark.impl.paramavg.BaseTrainingMaster
-
- storageLevel - Variable in class org.deeplearning4j.spark.impl.paramavg.ParameterAveragingTrainingMaster.Builder
-
- storageLevel(StorageLevel) - Method in class org.deeplearning4j.spark.impl.paramavg.ParameterAveragingTrainingMaster.Builder
-
Set the storage level for RDD<DataSet>s.
Default: StorageLevel.MEMORY_ONLY_SER() - i.e., store in memory, in serialized form
To use no RDD persistence, use null
- storageLevel - Variable in class org.deeplearning4j.spark.models.sequencevectors.SparkSequenceVectors.Builder
-
- storageLevel - Variable in class org.deeplearning4j.spark.models.sequencevectors.SparkSequenceVectors
-
- storageLevel - Variable in class org.deeplearning4j.spark.parameterserver.training.SharedTrainingMaster.Builder
-
- storageLevel(StorageLevel) - Method in class org.deeplearning4j.spark.parameterserver.training.SharedTrainingMaster.Builder
-
Set the storage level for RDD<DataSet>s.
Default: StorageLevel.MEMORY_ONLY_SER() - i.e., store in memory, in serialized form
To use no RDD persistence, use null
- storageLevel - Variable in class org.deeplearning4j.spark.parameterserver.training.SharedTrainingMaster
-
- StorageLevelDeserializer - Class in org.deeplearning4j.spark.util.serde
-
By default: Spark storage levels don't serialize/deserialize cleanly with Jackson (i.e., we can get different results out).
- StorageLevelDeserializer() - Constructor for class org.deeplearning4j.spark.util.serde.StorageLevelDeserializer
-
- StorageLevelSerializer - Class in org.deeplearning4j.spark.util.serde
-
By default: Spark storage levels don't serialize/deserialize cleanly with Jackson (i.e., we can get different results out).
- StorageLevelSerializer() - Constructor for class org.deeplearning4j.spark.util.serde.StorageLevelSerializer
-
- storageLevelStreams - Variable in class org.deeplearning4j.spark.impl.paramavg.BaseTrainingMaster
-
- storageLevelStreams - Variable in class org.deeplearning4j.spark.impl.paramavg.ParameterAveragingTrainingMaster.Builder
-
- storageLevelStreams(StorageLevel) - Method in class org.deeplearning4j.spark.impl.paramavg.ParameterAveragingTrainingMaster.Builder
-
- storageLevelStreams - Variable in class org.deeplearning4j.spark.parameterserver.training.SharedTrainingMaster.Builder
-
- StorageMetaData - Interface in org.deeplearning4j.api.storage
-
StorageMetaData: contains metadata (such at types, and arbitrary custom serializable data) for storage
- storageMetaData - Variable in class org.deeplearning4j.ui.storage.BaseCollectionStatsStorage
-
- StorageMetaDataDecoder - Class in org.deeplearning4j.ui.stats.sbe
-
- StorageMetaDataDecoder() - Constructor for class org.deeplearning4j.ui.stats.sbe.StorageMetaDataDecoder
-
- StorageMetaDataDecoder.ExtraMetaDataBytesDecoder - Class in org.deeplearning4j.ui.stats.sbe
-
- StorageMetaDataEncoder - Class in org.deeplearning4j.ui.stats.sbe
-
- StorageMetaDataEncoder() - Constructor for class org.deeplearning4j.ui.stats.sbe.StorageMetaDataEncoder
-
- StorageMetaDataEncoder.ExtraMetaDataBytesEncoder - Class in org.deeplearning4j.ui.stats.sbe
-
- storageRouter - Variable in class org.deeplearning4j.parallelism.ParallelWrapper
-
- StorageType - Enum in org.deeplearning4j.api.storage
-
Type of storage information
- storeLabel(String) - Method in class org.deeplearning4j.text.documentiterator.LabelsSource
-
This method is intended for storing labels retrieved from external sources.
- storeUpdate(INDArray) - Method in class org.deeplearning4j.optimize.solvers.accumulation.BasicGradientsAccumulator
-
This method accepts updates suitable for StepFunction, and accumulates/propagates it across all workers
- storeUpdate(INDArray) - Method in class org.deeplearning4j.optimize.solvers.accumulation.EncodedGradientsAccumulator
-
This method accepts updates suitable for StepFunction, and accumulates/propagates it across all workers
- storeUpdate(INDArray) - Method in interface org.deeplearning4j.optimize.solvers.accumulation.GradientsAccumulator
-
This method accepts updates suitable for StepFunction, and accumulates/propagates it across all workers
- stream(String) - Static method in class org.ansj.dic.PathToStream
-
- stream - Variable in class org.deeplearning4j.models.embeddings.loader.WordVectorSerializer.BinaryReader
-
- StreamingPipeline - Class in org.deeplearning4j
-
Created by agibsoncccc on 6/6/16.
- StreamingPipeline() - Constructor for class org.deeplearning4j.StreamingPipeline
-
- StreamLineIterator - Class in org.deeplearning4j.text.sentenceiterator
-
Simple class suitable for iterating over InputStreams as over lines of strings
Please note, this class is NOT thread safe
- StreamLineIterator.Builder - Class in org.deeplearning4j.text.sentenceiterator
-
- StreamWork - Class in org.deeplearning4j.models.word2vec
-
- StreamWork(InputStreamCreator, AtomicInteger) - Constructor for class org.deeplearning4j.models.word2vec.StreamWork
-
- stride(int) - Method in class org.deeplearning4j.nn.conf.layers.Convolution1DLayer.Builder
-
- stride(int...) - Method in class org.deeplearning4j.nn.conf.layers.Convolution3D.Builder
-
Set stride size for 3D convolutions in (depth, height, width) order
- stride - Variable in class org.deeplearning4j.nn.conf.layers.ConvolutionLayer.BaseConvBuilder
-
- stride(int...) - Method in class org.deeplearning4j.nn.conf.layers.ConvolutionLayer.Builder
-
- stride - Variable in class org.deeplearning4j.nn.conf.layers.ConvolutionLayer
-
- stride(int...) - Method in class org.deeplearning4j.nn.conf.layers.Deconvolution2D.Builder
-
- stride(int...) - Method in class org.deeplearning4j.nn.conf.layers.DepthwiseConvolution2D.Builder
-
- stride(int...) - Method in class org.deeplearning4j.nn.conf.layers.SeparableConvolution2D.Builder
-
- stride(int) - Method in class org.deeplearning4j.nn.conf.layers.Subsampling1DLayer.Builder
-
Stride
- stride - Variable in class org.deeplearning4j.nn.conf.layers.Subsampling3DLayer.BaseSubsamplingBuilder
-
- stride(int...) - Method in class org.deeplearning4j.nn.conf.layers.Subsampling3DLayer.Builder
-
Stride
- stride - Variable in class org.deeplearning4j.nn.conf.layers.Subsampling3DLayer
-
- stride - Variable in class org.deeplearning4j.nn.conf.layers.SubsamplingLayer.BaseSubsamplingBuilder
-
- stride(int...) - Method in class org.deeplearning4j.nn.conf.layers.SubsamplingLayer.Builder
-
Stride
- stride - Variable in class org.deeplearning4j.nn.conf.layers.SubsamplingLayer
-
- StringArrayIO - Class in com.atilika.kuromoji.io
-
- StringArrayIO() - Constructor for class com.atilika.kuromoji.io.StringArrayIO
-
- stringBuffer - Variable in class org.deeplearning4j.models.sequencevectors.transformers.impl.iterables.ParallelTransformerIterator
-
- StringCleaning - Class in org.deeplearning4j.text.tokenization.tokenizer.preprocessor
-
Various string cleaning utils
- StringKeyMapper() - Constructor for class com.atilika.kuromoji.trie.PatriciaTrie.StringKeyMapper
-
- stringSimilarity(String...) - Static method in class org.deeplearning4j.clustering.util.MathUtils
-
Calculate string similarity with tfidf weights relative to each character
frequency and how many times a character appears in a given string
- StringToDataSetExportFunction - Class in org.deeplearning4j.spark.datavec.export
-
A function (used in forEachPartition) to convert Strings to DataSet objects using a RecordReader (such as a CSVRecordReader).
- StringToDataSetExportFunction(URI, RecordReader, int, boolean, int, int) - Constructor for class org.deeplearning4j.spark.datavec.export.StringToDataSetExportFunction
-
- StringUtils - Class in com.atilika.kuromoji.util
-
- StringUtils() - Constructor for class com.atilika.kuromoji.util.StringUtils
-
- StringValueMapBuffer - Class in com.atilika.kuromoji.buffer
-
- StringValueMapBuffer(TreeMap<Integer, String>) - Constructor for class com.atilika.kuromoji.buffer.StringValueMapBuffer
-
- StringValueMapBuffer(InputStream) - Constructor for class com.atilika.kuromoji.buffer.StringValueMapBuffer
-
- stringValues - Variable in class com.atilika.kuromoji.dict.TokenInfoDictionary
-
- StringVertexFactory - Class in org.deeplearning4j.graph.vertexfactory
-
- StringVertexFactory() - Constructor for class org.deeplearning4j.graph.vertexfactory.StringVertexFactory
-
- StringVertexFactory(String) - Constructor for class org.deeplearning4j.graph.vertexfactory.StringVertexFactory
-
- stringWithLabels(String, TokenizerFactory) - Static method in class org.deeplearning4j.text.movingwindow.ContextLabelRetriever
-
Returns a stripped sentence with the indices of words
with certain kinds of labels.
- stripPunct(String) - Static method in class org.deeplearning4j.text.tokenization.tokenizer.preprocessor.StringCleaning
-
Removes ASCII punctuation marks, which are: 0123456789.:,"'()[]|/?!;
- strokeWidth - Variable in class org.deeplearning4j.ui.components.chart.style.StyleChart.Builder
-
- strokeWidth(double) - Method in class org.deeplearning4j.ui.components.chart.style.StyleChart.Builder
-
- strokeWidth - Variable in class org.deeplearning4j.ui.components.chart.style.StyleChart
-
- style - Variable in class org.deeplearning4j.ui.api.Component
-
- Style - Class in org.deeplearning4j.ui.api
-
Style defines things such as size of elements, an their margins.
- Style(Style.Builder) - Constructor for class org.deeplearning4j.ui.api.Style
-
- Style.Builder<T extends Style.Builder<T>> - Class in org.deeplearning4j.ui.api
-
- StyleAccordion - Class in org.deeplearning4j.ui.components.decorator.style
-
- StyleAccordion.Builder - Class in org.deeplearning4j.ui.components.decorator.style
-
- StyleChart - Class in org.deeplearning4j.ui.components.chart.style
-
Style for charts
- StyleChart.Builder - Class in org.deeplearning4j.ui.components.chart.style
-
- StyleDiv - Class in org.deeplearning4j.ui.components.component.style
-
Style for Div components.
- StyleDiv.Builder - Class in org.deeplearning4j.ui.components.component.style
-
- StyleDiv.FloatValue - Enum in org.deeplearning4j.ui.components.component.style
-
Enumeration: possible values for float style option
- StyleTable - Class in org.deeplearning4j.ui.components.table.style
-
Created by Alex on 3/04/2016.
- StyleTable.Builder - Class in org.deeplearning4j.ui.components.table.style
-
- StyleText - Class in org.deeplearning4j.ui.components.text.style
-
Style for text
- StyleText.Builder - Class in org.deeplearning4j.ui.components.text.style
-
- subDivide() - Method in class org.deeplearning4j.clustering.quadtree.QuadTree
-
Create four children
which fully divide this cell
into four quads of equal area
- subDivide() - Method in class org.deeplearning4j.clustering.sptree.SpTree
-
Subdivide the node in to
4 children
- subnetId(String) - Method in class org.deeplearning4j.aws.emr.SparkEMRClient.Builder
-
The id of the EC2 subnet to be used for this Spark EMR service
see https://docs.aws.amazon.com/AmazonVPC/latest/UserGuide/VPC_Subnets.html
- subsampling(double) - Method in class org.deeplearning4j.spark.models.sequencevectors.SparkSequenceVectors.Builder
-
- subsampling(double) - Method in class org.deeplearning4j.spark.models.word2vec.SparkWord2Vec.Builder
-
- Subsampling1DLayer - Class in org.deeplearning4j.nn.conf.layers
-
1D (temporal) subsampling layer.
- Subsampling1DLayer - Class in org.deeplearning4j.nn.layers.convolution.subsampling
-
1D (temporal) subsampling layer.
- Subsampling1DLayer(NeuralNetConfiguration) - Constructor for class org.deeplearning4j.nn.layers.convolution.subsampling.Subsampling1DLayer
-
- Subsampling1DLayer(NeuralNetConfiguration, INDArray) - Constructor for class org.deeplearning4j.nn.layers.convolution.subsampling.Subsampling1DLayer
-
- Subsampling1DLayer.Builder - Class in org.deeplearning4j.nn.conf.layers
-
- Subsampling3DLayer - Class in org.deeplearning4j.nn.conf.layers
-
3D subsampling / pooling layer for convolutional neural networks
- Subsampling3DLayer(Subsampling3DLayer.BaseSubsamplingBuilder) - Constructor for class org.deeplearning4j.nn.conf.layers.Subsampling3DLayer
-
- Subsampling3DLayer - Class in org.deeplearning4j.nn.layers.convolution.subsampling
-
Subsampling 3D layer, used for downsampling a 3D convolution
- Subsampling3DLayer(NeuralNetConfiguration) - Constructor for class org.deeplearning4j.nn.layers.convolution.subsampling.Subsampling3DLayer
-
- Subsampling3DLayer(NeuralNetConfiguration, INDArray) - Constructor for class org.deeplearning4j.nn.layers.convolution.subsampling.Subsampling3DLayer
-
- Subsampling3DLayer.BaseSubsamplingBuilder<T extends Subsampling3DLayer.BaseSubsamplingBuilder<T>> - Class in org.deeplearning4j.nn.conf.layers
-
- Subsampling3DLayer.Builder - Class in org.deeplearning4j.nn.conf.layers
-
- Subsampling3DLayer.PoolingType - Enum in org.deeplearning4j.nn.conf.layers
-
- SubsamplingHelper - Interface in org.deeplearning4j.nn.layers.convolution.subsampling
-
Helper for the subsampling layer.
- SubsamplingLayer - Class in org.deeplearning4j.nn.conf.layers
-
Subsampling layer also referred to as pooling in convolution neural nets
Supports the following pooling types: MAX, AVG, SUM, PNORM, NONE
- SubsamplingLayer(SubsamplingLayer.BaseSubsamplingBuilder) - Constructor for class org.deeplearning4j.nn.conf.layers.SubsamplingLayer
-
- SubsamplingLayer - Class in org.deeplearning4j.nn.layers.convolution.subsampling
-
Subsampling layer.
- SubsamplingLayer(NeuralNetConfiguration) - Constructor for class org.deeplearning4j.nn.layers.convolution.subsampling.SubsamplingLayer
-
- SubsamplingLayer(NeuralNetConfiguration, INDArray) - Constructor for class org.deeplearning4j.nn.layers.convolution.subsampling.SubsamplingLayer
-
- SubsamplingLayer.BaseSubsamplingBuilder<T extends SubsamplingLayer.BaseSubsamplingBuilder<T>> - Class in org.deeplearning4j.nn.conf.layers
-
- SubsamplingLayer.Builder - Class in org.deeplearning4j.nn.conf.layers
-
- SubsamplingLayer.PoolingType - Enum in org.deeplearning4j.nn.conf.layers
-
- SubsetVertex - Class in org.deeplearning4j.nn.conf.graph
-
SubsetVertex is used to select a subset of the activations out of another GraphVertex.
For example, a subset of the activations out of a layer.
Note that this subset is specifying by means of an interval of the original activations.
- SubsetVertex(int, int) - Constructor for class org.deeplearning4j.nn.conf.graph.SubsetVertex
-
- SubsetVertex - Class in org.deeplearning4j.nn.graph.vertex.impl
-
SubsetVertex is used to select a subset of the activations out of another GraphVertex.
For example, a subset of the activations out of a layer.
Note that this subset is specifying by means of an interval of the original activations.
- SubsetVertex(ComputationGraph, String, int, int, int) - Constructor for class org.deeplearning4j.nn.graph.vertex.impl.SubsetVertex
-
- SubsetVertex(ComputationGraph, String, int, VertexIndices[], VertexIndices[], int, int) - Constructor for class org.deeplearning4j.nn.graph.vertex.impl.SubsetVertex
-
- sum(double[]) - Static method in class org.ansj.util.MatrixUtil
-
向量求和
- sum(int[]) - Static method in class org.ansj.util.MatrixUtil
-
- sum(double[][]) - Static method in class org.ansj.util.MatrixUtil
-
- sum(double[]) - Static method in class org.deeplearning4j.clustering.util.MathUtils
-
This returns the sum of the given array.
- Summary - Class in org.ansj.app.summary.pojo
-
摘要结构体封装
- Summary(List<Keyword>, String) - Constructor for class org.ansj.app.summary.pojo.Summary
-
- summary() - Method in class org.deeplearning4j.nn.graph.ComputationGraph
-
String detailing the architecture of the computation graph.
- summary(InputType...) - Method in class org.deeplearning4j.nn.graph.ComputationGraph
-
String detailing the architecture of the computation graph.
- summary() - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
-
String detailing the architecture of the multilayernetwork.
- summary(InputType) - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
-
String detailing the architecture of the multilayernetwork.
- SummaryComputer - Class in org.ansj.app.summary
-
自动摘要,同时返回关键词
- SummaryComputer(String, String) - Constructor for class org.ansj.app.summary.SummaryComputer
-
- SummaryComputer(int, String, String) - Constructor for class org.ansj.app.summary.SummaryComputer
-
- SummaryComputer(int, boolean, String, String) - Constructor for class org.ansj.app.summary.SummaryComputer
-
- SummaryComputer.Sentence - Class in org.ansj.app.summary
-
- summaryStat() - Method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder.PerParameterStatsDecoder
-
- summaryStatCount(int) - Method in class org.deeplearning4j.ui.stats.sbe.UpdateEncoder.PerParameterStatsEncoder
-
- SummaryStatDecoder() - Constructor for class org.deeplearning4j.ui.stats.sbe.UpdateDecoder.PerParameterStatsDecoder.SummaryStatDecoder
-
- summaryStatDecoderId() - Static method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder.PerParameterStatsDecoder
-
- SummaryStatEncoder() - Constructor for class org.deeplearning4j.ui.stats.sbe.UpdateEncoder.PerParameterStatsEncoder.SummaryStatEncoder
-
- summaryStatId() - Static method in class org.deeplearning4j.ui.stats.sbe.UpdateEncoder.PerParameterStatsEncoder
-
- SummaryType - Enum in org.deeplearning4j.ui.stats.api
-
- SummaryType - Enum in org.deeplearning4j.ui.stats.sbe
-
- summaryType() - Method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder.PerParameterStatsDecoder.SummaryStatDecoder
-
- summaryType(SummaryType) - Method in class org.deeplearning4j.ui.stats.sbe.UpdateEncoder.PerParameterStatsEncoder.SummaryStatEncoder
-
- summaryTypeId() - Static method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder.PerParameterStatsDecoder.SummaryStatDecoder
-
- summaryTypeMetaAttribute(MetaAttribute) - Static method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder.PerParameterStatsDecoder.SummaryStatDecoder
-
- sumOfMeanDifferences(double[], double[]) - Static method in class org.deeplearning4j.clustering.util.MathUtils
-
Used for calculating top part of simple regression for
beta 1
- sumOfMeanDifferencesOnePoint(double[]) - Static method in class org.deeplearning4j.clustering.util.MathUtils
-
Used for calculating top part of simple regression for
beta 1
- sumOfProducts(double[]...) - Static method in class org.deeplearning4j.clustering.util.MathUtils
-
This returns the sum of products for the given
numbers.
- sumOfSquares(double[]) - Static method in class org.deeplearning4j.clustering.util.MathUtils
-
This returns the sum of squares for the given vector.
- suppressAxisHorizontal(boolean) - Method in class org.deeplearning4j.ui.components.chart.Chart.Builder
-
- suppressAxisVertical(boolean) - Method in class org.deeplearning4j.ui.components.chart.Chart.Builder
-
- surface - Variable in class com.atilika.kuromoji.dict.DictionaryEntryBase
-
- SURFACE - Static variable in class com.atilika.kuromoji.dict.DictionaryField
-
- surface(String) - Method in class com.atilika.kuromoji.dict.GenericDictionaryEntry.Builder
-
- SvhnDataFetcher - Class in org.deeplearning4j.datasets.fetchers
-
The Street View House Numbers (SVHN) Dataset is a real-world image dataset for developing machine learning
and object recognition algorithms with minimal requirement on data preprocessing and formatting.
- SvhnDataFetcher() - Constructor for class org.deeplearning4j.datasets.fetchers.SvhnDataFetcher
-
- swArch() - Method in class org.deeplearning4j.ui.stats.sbe.StaticInfoDecoder
-
- swArch(String) - Method in class org.deeplearning4j.ui.stats.sbe.StaticInfoEncoder
-
- swArchCharacterEncoding() - Static method in class org.deeplearning4j.ui.stats.sbe.StaticInfoDecoder
-
- swArchCharacterEncoding() - Static method in class org.deeplearning4j.ui.stats.sbe.StaticInfoEncoder
-
- swArchHeaderLength() - Static method in class org.deeplearning4j.ui.stats.sbe.StaticInfoDecoder
-
- swArchHeaderLength() - Static method in class org.deeplearning4j.ui.stats.sbe.StaticInfoEncoder
-
- swArchId() - Static method in class org.deeplearning4j.ui.stats.sbe.StaticInfoDecoder
-
- swArchId() - Static method in class org.deeplearning4j.ui.stats.sbe.StaticInfoEncoder
-
- swArchLength() - Method in class org.deeplearning4j.ui.stats.sbe.StaticInfoDecoder
-
- swArchMetaAttribute(MetaAttribute) - Static method in class org.deeplearning4j.ui.stats.sbe.StaticInfoDecoder
-
- swArchMetaAttribute(MetaAttribute) - Static method in class org.deeplearning4j.ui.stats.sbe.StaticInfoEncoder
-
- swEnvironmentInfo() - Method in class org.deeplearning4j.ui.stats.sbe.StaticInfoDecoder
-
- swEnvironmentInfoCount(int) - Method in class org.deeplearning4j.ui.stats.sbe.StaticInfoEncoder
-
- SwEnvironmentInfoDecoder() - Constructor for class org.deeplearning4j.ui.stats.sbe.StaticInfoDecoder.SwEnvironmentInfoDecoder
-
- swEnvironmentInfoDecoderId() - Static method in class org.deeplearning4j.ui.stats.sbe.StaticInfoDecoder
-
- SwEnvironmentInfoEncoder() - Constructor for class org.deeplearning4j.ui.stats.sbe.StaticInfoEncoder.SwEnvironmentInfoEncoder
-
- swEnvironmentInfoId() - Static method in class org.deeplearning4j.ui.stats.sbe.StaticInfoEncoder
-
- swHostName() - Method in class org.deeplearning4j.ui.stats.sbe.StaticInfoDecoder
-
- swHostName(String) - Method in class org.deeplearning4j.ui.stats.sbe.StaticInfoEncoder
-
- swHostNameCharacterEncoding() - Static method in class org.deeplearning4j.ui.stats.sbe.StaticInfoDecoder
-
- swHostNameCharacterEncoding() - Static method in class org.deeplearning4j.ui.stats.sbe.StaticInfoEncoder
-
- swHostNameHeaderLength() - Static method in class org.deeplearning4j.ui.stats.sbe.StaticInfoDecoder
-
- swHostNameHeaderLength() - Static method in class org.deeplearning4j.ui.stats.sbe.StaticInfoEncoder
-
- swHostNameId() - Static method in class org.deeplearning4j.ui.stats.sbe.StaticInfoDecoder
-
- swHostNameId() - Static method in class org.deeplearning4j.ui.stats.sbe.StaticInfoEncoder
-
- swHostNameLength() - Method in class org.deeplearning4j.ui.stats.sbe.StaticInfoDecoder
-
- swHostNameMetaAttribute(MetaAttribute) - Static method in class org.deeplearning4j.ui.stats.sbe.StaticInfoDecoder
-
- swHostNameMetaAttribute(MetaAttribute) - Static method in class org.deeplearning4j.ui.stats.sbe.StaticInfoEncoder
-
- switchMomentumIteration - Variable in class org.deeplearning4j.plot.BarnesHutTsne
-
- switchMomentumIteration - Variable in class org.deeplearning4j.plot.Tsne.Builder
-
- switchMomentumIteration - Variable in class org.deeplearning4j.plot.Tsne
-
- swJvmName() - Method in class org.deeplearning4j.ui.stats.sbe.StaticInfoDecoder
-
- swJvmName(String) - Method in class org.deeplearning4j.ui.stats.sbe.StaticInfoEncoder
-
- swJvmNameCharacterEncoding() - Static method in class org.deeplearning4j.ui.stats.sbe.StaticInfoDecoder
-
- swJvmNameCharacterEncoding() - Static method in class org.deeplearning4j.ui.stats.sbe.StaticInfoEncoder
-
- swJvmNameHeaderLength() - Static method in class org.deeplearning4j.ui.stats.sbe.StaticInfoDecoder
-
- swJvmNameHeaderLength() - Static method in class org.deeplearning4j.ui.stats.sbe.StaticInfoEncoder
-
- swJvmNameId() - Static method in class org.deeplearning4j.ui.stats.sbe.StaticInfoDecoder
-
- swJvmNameId() - Static method in class org.deeplearning4j.ui.stats.sbe.StaticInfoEncoder
-
- swJvmNameLength() - Method in class org.deeplearning4j.ui.stats.sbe.StaticInfoDecoder
-
- swJvmNameMetaAttribute(MetaAttribute) - Static method in class org.deeplearning4j.ui.stats.sbe.StaticInfoDecoder
-
- swJvmNameMetaAttribute(MetaAttribute) - Static method in class org.deeplearning4j.ui.stats.sbe.StaticInfoEncoder
-
- swJvmSpecVersion() - Method in class org.deeplearning4j.ui.stats.sbe.StaticInfoDecoder
-
- swJvmSpecVersion(String) - Method in class org.deeplearning4j.ui.stats.sbe.StaticInfoEncoder
-
- swJvmSpecVersionCharacterEncoding() - Static method in class org.deeplearning4j.ui.stats.sbe.StaticInfoDecoder
-
- swJvmSpecVersionCharacterEncoding() - Static method in class org.deeplearning4j.ui.stats.sbe.StaticInfoEncoder
-
- swJvmSpecVersionHeaderLength() - Static method in class org.deeplearning4j.ui.stats.sbe.StaticInfoDecoder
-
- swJvmSpecVersionHeaderLength() - Static method in class org.deeplearning4j.ui.stats.sbe.StaticInfoEncoder
-
- swJvmSpecVersionId() - Static method in class org.deeplearning4j.ui.stats.sbe.StaticInfoDecoder
-
- swJvmSpecVersionId() - Static method in class org.deeplearning4j.ui.stats.sbe.StaticInfoEncoder
-
- swJvmSpecVersionLength() - Method in class org.deeplearning4j.ui.stats.sbe.StaticInfoDecoder
-
- swJvmSpecVersionMetaAttribute(MetaAttribute) - Static method in class org.deeplearning4j.ui.stats.sbe.StaticInfoDecoder
-
- swJvmSpecVersionMetaAttribute(MetaAttribute) - Static method in class org.deeplearning4j.ui.stats.sbe.StaticInfoEncoder
-
- swJvmUID() - Method in class org.deeplearning4j.ui.stats.sbe.StaticInfoDecoder
-
- swJvmUID(String) - Method in class org.deeplearning4j.ui.stats.sbe.StaticInfoEncoder
-
- swJvmUIDCharacterEncoding() - Static method in class org.deeplearning4j.ui.stats.sbe.StaticInfoDecoder
-
- swJvmUIDCharacterEncoding() - Static method in class org.deeplearning4j.ui.stats.sbe.StaticInfoEncoder
-
- swJvmUIDHeaderLength() - Static method in class org.deeplearning4j.ui.stats.sbe.StaticInfoDecoder
-
- swJvmUIDHeaderLength() - Static method in class org.deeplearning4j.ui.stats.sbe.StaticInfoEncoder
-
- swJvmUIDId() - Static method in class org.deeplearning4j.ui.stats.sbe.StaticInfoDecoder
-
- swJvmUIDId() - Static method in class org.deeplearning4j.ui.stats.sbe.StaticInfoEncoder
-
- swJvmUIDLength() - Method in class org.deeplearning4j.ui.stats.sbe.StaticInfoDecoder
-
- swJvmUIDMetaAttribute(MetaAttribute) - Static method in class org.deeplearning4j.ui.stats.sbe.StaticInfoDecoder
-
- swJvmUIDMetaAttribute(MetaAttribute) - Static method in class org.deeplearning4j.ui.stats.sbe.StaticInfoEncoder
-
- swJvmVersion() - Method in class org.deeplearning4j.ui.stats.sbe.StaticInfoDecoder
-
- swJvmVersion(String) - Method in class org.deeplearning4j.ui.stats.sbe.StaticInfoEncoder
-
- swJvmVersionCharacterEncoding() - Static method in class org.deeplearning4j.ui.stats.sbe.StaticInfoDecoder
-
- swJvmVersionCharacterEncoding() - Static method in class org.deeplearning4j.ui.stats.sbe.StaticInfoEncoder
-
- swJvmVersionHeaderLength() - Static method in class org.deeplearning4j.ui.stats.sbe.StaticInfoDecoder
-
- swJvmVersionHeaderLength() - Static method in class org.deeplearning4j.ui.stats.sbe.StaticInfoEncoder
-
- swJvmVersionId() - Static method in class org.deeplearning4j.ui.stats.sbe.StaticInfoDecoder
-
- swJvmVersionId() - Static method in class org.deeplearning4j.ui.stats.sbe.StaticInfoEncoder
-
- swJvmVersionLength() - Method in class org.deeplearning4j.ui.stats.sbe.StaticInfoDecoder
-
- swJvmVersionMetaAttribute(MetaAttribute) - Static method in class org.deeplearning4j.ui.stats.sbe.StaticInfoDecoder
-
- swJvmVersionMetaAttribute(MetaAttribute) - Static method in class org.deeplearning4j.ui.stats.sbe.StaticInfoEncoder
-
- SWN3 - Class in org.deeplearning4j.text.corpora.sentiwordnet
-
Based on SentiWordnet
- SWN3() - Constructor for class org.deeplearning4j.text.corpora.sentiwordnet.SWN3
-
- SWN3(AnalysisEngine) - Constructor for class org.deeplearning4j.text.corpora.sentiwordnet.SWN3
-
- SWN3(String) - Constructor for class org.deeplearning4j.text.corpora.sentiwordnet.SWN3
-
- swNd4jBackendClass() - Method in class org.deeplearning4j.ui.stats.sbe.StaticInfoDecoder
-
- swNd4jBackendClass(String) - Method in class org.deeplearning4j.ui.stats.sbe.StaticInfoEncoder
-
- swNd4jBackendClassCharacterEncoding() - Static method in class org.deeplearning4j.ui.stats.sbe.StaticInfoDecoder
-
- swNd4jBackendClassCharacterEncoding() - Static method in class org.deeplearning4j.ui.stats.sbe.StaticInfoEncoder
-
- swNd4jBackendClassHeaderLength() - Static method in class org.deeplearning4j.ui.stats.sbe.StaticInfoDecoder
-
- swNd4jBackendClassHeaderLength() - Static method in class org.deeplearning4j.ui.stats.sbe.StaticInfoEncoder
-
- swNd4jBackendClassId() - Static method in class org.deeplearning4j.ui.stats.sbe.StaticInfoDecoder
-
- swNd4jBackendClassId() - Static method in class org.deeplearning4j.ui.stats.sbe.StaticInfoEncoder
-
- swNd4jBackendClassLength() - Method in class org.deeplearning4j.ui.stats.sbe.StaticInfoDecoder
-
- swNd4jBackendClassMetaAttribute(MetaAttribute) - Static method in class org.deeplearning4j.ui.stats.sbe.StaticInfoDecoder
-
- swNd4jBackendClassMetaAttribute(MetaAttribute) - Static method in class org.deeplearning4j.ui.stats.sbe.StaticInfoEncoder
-
- swNd4jDataTypeName() - Method in class org.deeplearning4j.ui.stats.sbe.StaticInfoDecoder
-
- swNd4jDataTypeName(String) - Method in class org.deeplearning4j.ui.stats.sbe.StaticInfoEncoder
-
- swNd4jDataTypeNameCharacterEncoding() - Static method in class org.deeplearning4j.ui.stats.sbe.StaticInfoDecoder
-
- swNd4jDataTypeNameCharacterEncoding() - Static method in class org.deeplearning4j.ui.stats.sbe.StaticInfoEncoder
-
- swNd4jDataTypeNameHeaderLength() - Static method in class org.deeplearning4j.ui.stats.sbe.StaticInfoDecoder
-
- swNd4jDataTypeNameHeaderLength() - Static method in class org.deeplearning4j.ui.stats.sbe.StaticInfoEncoder
-
- swNd4jDataTypeNameId() - Static method in class org.deeplearning4j.ui.stats.sbe.StaticInfoDecoder
-
- swNd4jDataTypeNameId() - Static method in class org.deeplearning4j.ui.stats.sbe.StaticInfoEncoder
-
- swNd4jDataTypeNameLength() - Method in class org.deeplearning4j.ui.stats.sbe.StaticInfoDecoder
-
- swNd4jDataTypeNameMetaAttribute(MetaAttribute) - Static method in class org.deeplearning4j.ui.stats.sbe.StaticInfoDecoder
-
- swNd4jDataTypeNameMetaAttribute(MetaAttribute) - Static method in class org.deeplearning4j.ui.stats.sbe.StaticInfoEncoder
-
- swOsName() - Method in class org.deeplearning4j.ui.stats.sbe.StaticInfoDecoder
-
- swOsName(String) - Method in class org.deeplearning4j.ui.stats.sbe.StaticInfoEncoder
-
- swOsNameCharacterEncoding() - Static method in class org.deeplearning4j.ui.stats.sbe.StaticInfoDecoder
-
- swOsNameCharacterEncoding() - Static method in class org.deeplearning4j.ui.stats.sbe.StaticInfoEncoder
-
- swOsNameHeaderLength() - Static method in class org.deeplearning4j.ui.stats.sbe.StaticInfoDecoder
-
- swOsNameHeaderLength() - Static method in class org.deeplearning4j.ui.stats.sbe.StaticInfoEncoder
-
- swOsNameId() - Static method in class org.deeplearning4j.ui.stats.sbe.StaticInfoDecoder
-
- swOsNameId() - Static method in class org.deeplearning4j.ui.stats.sbe.StaticInfoEncoder
-
- swOsNameLength() - Method in class org.deeplearning4j.ui.stats.sbe.StaticInfoDecoder
-
- swOsNameMetaAttribute(MetaAttribute) - Static method in class org.deeplearning4j.ui.stats.sbe.StaticInfoDecoder
-
- swOsNameMetaAttribute(MetaAttribute) - Static method in class org.deeplearning4j.ui.stats.sbe.StaticInfoEncoder
-
- symmetric - Variable in class org.deeplearning4j.models.embeddings.learning.impl.elements.GloVe.Builder
-
- symmetric(boolean) - Method in class org.deeplearning4j.models.embeddings.learning.impl.elements.GloVe.Builder
-
Parameters specifying, if cooccurrences list should be build into both directions from any current word.
- symmetric - Variable in class org.deeplearning4j.models.glove.AbstractCoOccurrences.Builder
-
- symmetric(boolean) - Method in class org.deeplearning4j.models.glove.AbstractCoOccurrences.Builder
-
- symmetric - Variable in class org.deeplearning4j.models.glove.AbstractCoOccurrences
-
- symmetric(boolean) - Method in class org.deeplearning4j.models.glove.Glove.Builder
-
Parameters specifying, if cooccurrences list should be build into both directions from any current word.
- SymmetricTrainer - Class in org.deeplearning4j.parallelism.trainer
-
This trainer implementation does parallel training via gradients broadcasts.
- SymmetricTrainer(Model, String, int, WorkspaceMode, ParallelWrapper, boolean) - Constructor for class org.deeplearning4j.parallelism.trainer.SymmetricTrainer
-
- SymmetricTrainerContext - Class in org.deeplearning4j.parallelism.factory
-
- SymmetricTrainerContext() - Constructor for class org.deeplearning4j.parallelism.factory.SymmetricTrainerContext
-
- symmetrized(INDArray, INDArray, INDArray) - Method in class org.deeplearning4j.plot.BarnesHutTsne
-
Symmetrize the value matrix
- syn0 - Variable in class org.deeplearning4j.models.embeddings.inmemory.InMemoryLookupTable
-
- syn0 - Variable in class org.deeplearning4j.models.embeddings.learning.impl.elements.CBOW
-
- syn0 - Variable in class org.deeplearning4j.models.embeddings.learning.impl.elements.SkipGram
-
- syn0 - Variable in class org.deeplearning4j.models.embeddings.learning.impl.sequence.DM
-
- syn1 - Variable in class org.deeplearning4j.models.embeddings.inmemory.InMemoryLookupTable
-
- syn1 - Variable in class org.deeplearning4j.models.embeddings.learning.impl.elements.CBOW
-
- syn1 - Variable in class org.deeplearning4j.models.embeddings.learning.impl.elements.SkipGram
-
- syn1 - Variable in class org.deeplearning4j.models.embeddings.learning.impl.sequence.DM
-
- syn1Neg - Variable in class org.deeplearning4j.models.embeddings.inmemory.InMemoryLookupTable
-
- syn1Neg - Variable in class org.deeplearning4j.models.embeddings.learning.impl.elements.CBOW
-
- syn1Neg - Variable in class org.deeplearning4j.models.embeddings.learning.impl.elements.SkipGram
-
- syn1Neg - Variable in class org.deeplearning4j.models.embeddings.learning.impl.sequence.DM
-
- synchronize(int) - Method in class org.deeplearning4j.optimize.solvers.accumulation.EncodedGradientsAccumulator
-
- synchronize(int, boolean) - Method in class org.deeplearning4j.optimize.solvers.accumulation.EncodedGradientsAccumulator
-
- synchronize(int) - Method in class org.deeplearning4j.optimize.solvers.accumulation.FancyBlockingQueue
-
- SynchronizedSentenceIterator - Class in org.deeplearning4j.text.sentenceiterator
-
Simple synchronized wrapper for SentenceIterator interface implementations
- SynchronizedSentenceIterator(SentenceIterator) - Constructor for class org.deeplearning4j.text.sentenceiterator.SynchronizedSentenceIterator
-
- SynchronizedSequenceIterator<T extends SequenceElement> - Class in org.deeplearning4j.models.sequencevectors.iterators
-
Synchronized version of AbstractSeuqenceIterator, implemented on top of it.
- SynchronizedSequenceIterator(SequenceIterator<T>) - Constructor for class org.deeplearning4j.models.sequencevectors.iterators.SynchronizedSequenceIterator
-
Creates SynchronizedSequenceIterator on top of any SequenceIterator
- synchronizeIterEpochCounts() - Method in class org.deeplearning4j.nn.graph.ComputationGraph
-
- synchronizeIterEpochCounts() - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
-
- SynonymsLibrary - Class in org.ansj.library
-
- SynonymsLibrary() - Constructor for class org.ansj.library.SynonymsLibrary
-
- SynonymsRecgnition - Class in org.ansj.recognition.impl
-
同义词功能
- SynonymsRecgnition() - Constructor for class org.ansj.recognition.impl.SynonymsRecgnition
-
- SynonymsRecgnition(String) - Constructor for class org.ansj.recognition.impl.SynonymsRecgnition
-
- SynonymsRecgnition(SmartForest<List<String>>) - Constructor for class org.ansj.recognition.impl.SynonymsRecgnition
-
- SystemClockTimeSource - Class in org.deeplearning4j.spark.time
-
- SystemClockTimeSource() - Constructor for class org.deeplearning4j.spark.time.SystemClockTimeSource
-
- SystemInfoFilePrintListener - Class in org.deeplearning4j.perf.listener
-
Using SystemInfo - it prints a json representation
on each callback to the specified file.
- SystemInfoFilePrintListener(boolean, boolean, boolean, boolean, boolean, File) - Constructor for class org.deeplearning4j.perf.listener.SystemInfoFilePrintListener
-
- SystemInfoPrintListener - Class in org.deeplearning4j.perf.listener
-
Using SystemInfo - it logs a json representation
of system info using slf4j.
- SystemInfoPrintListener() - Constructor for class org.deeplearning4j.perf.listener.SystemInfoPrintListener
-
- SystemInfoTest - Class in org.deeplearning4j.perf.listener
-
The Class SystemInfoTest.
- SystemInfoTest() - Constructor for class org.deeplearning4j.perf.listener.SystemInfoTest
-
- SystemPolling - Class in org.deeplearning4j.perf.listener
-
Poll a system for its local statistics with a specified time.
- SystemPolling.Builder - Class in org.deeplearning4j.perf.listener
-
- SystemPolling.NameProvider - Interface in org.deeplearning4j.perf.listener
-
The naming sequence provider.
- table - Variable in class org.deeplearning4j.models.embeddings.inmemory.InMemoryLookupTable
-
- table - Variable in class org.deeplearning4j.models.embeddings.learning.impl.elements.CBOW
-
- table - Variable in class org.deeplearning4j.models.embeddings.learning.impl.elements.SkipGram
-
- table - Variable in class org.deeplearning4j.models.embeddings.learning.impl.sequence.DM
-
- table(INDArray) - Method in class org.deeplearning4j.spark.models.embeddings.word2vec.Word2VecParam.Builder
-
Deprecated.
- TABLE - Static variable in class org.deeplearning4j.spark.models.embeddings.word2vec.Word2VecPerformerVoid
-
Deprecated.
- TABLE - Static variable in class org.deeplearning4j.spark.models.embeddings.word2vec.Word2VecVariables
-
Deprecated.
- tableId - Variable in class org.deeplearning4j.models.embeddings.inmemory.InMemoryLookupTable
-
- TAG_NUM - Static variable in class org.ansj.app.crf.Config
-
- TagContent - Class in org.ansj.app.summary
-
关键字标红，
- TagContent(String, String) - Constructor for class org.ansj.app.summary.TagContent
-
- tagContent(Summary) - Method in class org.ansj.app.summary.TagContent
-
- tagContent(List<Keyword>, String) - Method in class org.ansj.app.summary.TagContent
-
- tagger - Variable in class org.deeplearning4j.models.sequencevectors.iterators.AbstractSequenceIterator
-
- tagRate(int, int) - Method in class org.ansj.app.crf.Model
-
tag转移率
- tags() - Method in class org.deeplearning4j.nn.layers.feedforward.autoencoder.recursive.Tree
-
- tagScore - Variable in class org.ansj.app.crf.pojo.Element
-
- take() - Method in class org.deeplearning4j.optimize.solvers.accumulation.FancyBlockingQueue
-
- take() - Method in class org.deeplearning4j.parallelism.MagicQueue
-
Deprecated.
- target - Variable in class org.deeplearning4j.models.glove.AbstractCoOccurrences.Builder
-
- targetFile(String) - Method in class org.deeplearning4j.models.glove.AbstractCoOccurrences.Builder
-
Path to save cooccurrence map after construction.
- targetFile(File) - Method in class org.deeplearning4j.models.glove.AbstractCoOccurrences.Builder
-
Path to save cooccurrence map after construction.
- targetFile - Variable in class org.deeplearning4j.models.glove.AbstractCoOccurrences
-
- TARGETMAP_FILENAME - Static variable in class com.atilika.kuromoji.dict.TokenInfoDictionary
-
- targetMessageClass() - Method in class org.deeplearning4j.spark.parameterserver.networking.SilentTrainingDriver
-
- taskByModel(Model) - Static method in class org.deeplearning4j.util.ModelSerializer
-
- tbpttBackLength - Variable in class org.deeplearning4j.nn.conf.ComputationGraphConfiguration.GraphBuilder
-
- tbpttBackLength - Variable in class org.deeplearning4j.nn.conf.ComputationGraphConfiguration
-
- tbpttBackLength - Variable in class org.deeplearning4j.nn.conf.MultiLayerConfiguration.Builder
-
- tbpttBackLength - Variable in class org.deeplearning4j.nn.conf.MultiLayerConfiguration
-
- tbpttBackLength(int) - Method in class org.deeplearning4j.nn.transferlearning.FineTuneConfiguration.Builder
-
When doing truncated BPTT: how many steps of backward should we do?
Only applicable when doing backpropType(BackpropType.TruncatedBPTT)
This is the k2 parameter on pg23 of
http://www.cs.utoronto.ca/~ilya/pubs/ilya_sutskever_phd_thesis.pdf
- tbpttBackLength - Variable in class org.deeplearning4j.nn.transferlearning.FineTuneConfiguration
-
- tbpttBackpropGradient(INDArray, int, LayerWorkspaceMgr) - Method in interface org.deeplearning4j.nn.api.layers.RecurrentLayer
-
Truncated BPTT equivalent of Layer.backpropGradient().
- tbpttBackpropGradient(INDArray, int, LayerWorkspaceMgr) - Method in class org.deeplearning4j.nn.layers.recurrent.BidirectionalLayer
-
- tbpttBackpropGradient(INDArray, int, LayerWorkspaceMgr) - Method in class org.deeplearning4j.nn.layers.recurrent.GravesBidirectionalLSTM
-
- tbpttBackpropGradient(INDArray, int, LayerWorkspaceMgr) - Method in class org.deeplearning4j.nn.layers.recurrent.GravesLSTM
-
- tbpttBackpropGradient(INDArray, int, LayerWorkspaceMgr) - Method in class org.deeplearning4j.nn.layers.recurrent.LSTM
-
- tbpttBackpropGradient(INDArray, int, LayerWorkspaceMgr) - Method in class org.deeplearning4j.nn.layers.recurrent.SimpleRnn
-
- tBPTTBackwardLength(int) - Method in class org.deeplearning4j.nn.conf.ComputationGraphConfiguration.GraphBuilder
-
When doing truncated BPTT: how many steps of backward should we do?
Only applicable when doing backpropType(BackpropType.TruncatedBPTT)
This is the k2 parameter on pg23 of
http://www.cs.utoronto.ca/~ilya/pubs/ilya_sutskever_phd_thesis.pdf
- tBPTTBackwardLength(int) - Method in class org.deeplearning4j.nn.conf.MultiLayerConfiguration.Builder
-
When doing truncated BPTT: how many steps of backward should we do?
Only applicable when doing backpropType(BackpropType.TruncatedBPTT)
This is the k2 parameter on pg23 of
http://www.cs.utoronto.ca/~ilya/pubs/ilya_sutskever_phd_thesis.pdf
- tBPTTForwardLength(int) - Method in class org.deeplearning4j.nn.conf.ComputationGraphConfiguration.GraphBuilder
-
When doing truncated BPTT: how many steps of forward pass should we do
before doing (truncated) backprop?
Only applicable when doing backpropType(BackpropType.TruncatedBPTT)
Typically tBPTTForwardLength parameter is same as the tBPTTBackwardLength parameter,
but may be larger than it in some circumstances (but never smaller)
Ideally your training data time series length should be divisible by this
This is the k1 parameter on pg23 of
http://www.cs.utoronto.ca/~ilya/pubs/ilya_sutskever_phd_thesis.pdf
- tBPTTForwardLength(int) - Method in class org.deeplearning4j.nn.conf.MultiLayerConfiguration.Builder
-
When doing truncated BPTT: how many steps of forward pass should we do
before doing (truncated) backprop?
Only applicable when doing backpropType(BackpropType.TruncatedBPTT)
Typically tBPTTForwardLength parameter is same as the tBPTTBackwardLength parameter,
but may be larger than it in some circumstances (but never smaller)
Ideally your training data time series length should be divisible by this
This is the k1 parameter on pg23 of
http://www.cs.utoronto.ca/~ilya/pubs/ilya_sutskever_phd_thesis.pdf
- tbpttFwdLength - Variable in class org.deeplearning4j.nn.conf.ComputationGraphConfiguration.GraphBuilder
-
- tbpttFwdLength - Variable in class org.deeplearning4j.nn.conf.ComputationGraphConfiguration
-
- tbpttFwdLength - Variable in class org.deeplearning4j.nn.conf.MultiLayerConfiguration.Builder
-
- tbpttFwdLength - Variable in class org.deeplearning4j.nn.conf.MultiLayerConfiguration
-
- tbpttFwdLength(int) - Method in class org.deeplearning4j.nn.transferlearning.FineTuneConfiguration.Builder
-
When doing truncated BPTT: how many steps of forward pass should we do
before doing (truncated) backprop?
Only applicable when doing backpropType(BackpropType.TruncatedBPTT)
Typically tBPTTForwardLength parameter is same as the tBPTTBackwardLength parameter,
but may be larger than it in some circumstances (but never smaller)
Ideally your training data time series length should be divisible by this
This is the k1 parameter on pg23 of
http://www.cs.utoronto.ca/~ilya/pubs/ilya_sutskever_phd_thesis.pdf
- tbpttFwdLength - Variable in class org.deeplearning4j.nn.transferlearning.FineTuneConfiguration
-
- tBPTTLength(int) - Method in class org.deeplearning4j.nn.conf.ComputationGraphConfiguration.GraphBuilder
-
When doing truncated backpropagation through time (tBPTT): how many steps should we do?
Only applicable when doing backpropType(BackpropType.TruncatedBPTT)
See: http://www.cs.utoronto.ca/~ilya/pubs/ilya_sutskever_phd_thesis.pdf
- tBPTTLength(int) - Method in class org.deeplearning4j.nn.conf.MultiLayerConfiguration.Builder
-
When doing truncated BPTT: how many steps should we do?
Only applicable when doing backpropType(BackpropType.TruncatedBPTT)
See: http://www.cs.utoronto.ca/~ilya/pubs/ilya_sutskever_phd_thesis.pdf
- tBpttStateMap - Variable in class org.deeplearning4j.nn.layers.recurrent.BaseRecurrentLayer
-
State map for use specifically in truncated BPTT training.
- TEMP_ROOT - Static variable in class com.atilika.kuromoji.util.KuromojiBinFilesFetcher
-
- TEMP_ROOT - Static variable in class org.deeplearning4j.datasets.fetchers.MnistDataFetcher
-
- template - Variable in class org.deeplearning4j.optimize.listeners.callbacks.ModelSavingCallback
-
- TEMPLATE_ID - Static variable in class org.deeplearning4j.ui.stats.sbe.StaticInfoDecoder
-
- TEMPLATE_ID - Static variable in class org.deeplearning4j.ui.stats.sbe.StaticInfoEncoder
-
- TEMPLATE_ID - Static variable in class org.deeplearning4j.ui.stats.sbe.StorageMetaDataDecoder
-
- TEMPLATE_ID - Static variable in class org.deeplearning4j.ui.stats.sbe.StorageMetaDataEncoder
-
- TEMPLATE_ID - Static variable in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder
-
- TEMPLATE_ID - Static variable in class org.deeplearning4j.ui.stats.sbe.UpdateEncoder
-
- templateId() - Method in class org.deeplearning4j.ui.stats.sbe.MessageHeaderDecoder
-
- templateId(int) - Method in class org.deeplearning4j.ui.stats.sbe.MessageHeaderEncoder
-
- templateIdMaxValue() - Static method in class org.deeplearning4j.ui.stats.sbe.MessageHeaderDecoder
-
- templateIdMaxValue() - Static method in class org.deeplearning4j.ui.stats.sbe.MessageHeaderEncoder
-
- templateIdMinValue() - Static method in class org.deeplearning4j.ui.stats.sbe.MessageHeaderDecoder
-
- templateIdMinValue() - Static method in class org.deeplearning4j.ui.stats.sbe.MessageHeaderEncoder
-
- templateIdNullValue() - Static method in class org.deeplearning4j.ui.stats.sbe.MessageHeaderDecoder
-
- templateIdNullValue() - Static method in class org.deeplearning4j.ui.stats.sbe.MessageHeaderEncoder
-
- TENSOR_FORMAT - Static variable in class org.deeplearning4j.nn.layers.BaseCudnnHelper
-
- TensorArray() - Constructor for class org.deeplearning4j.nn.layers.BaseCudnnHelper.TensorArray
-
- TensorArray(long) - Constructor for class org.deeplearning4j.nn.layers.BaseCudnnHelper.TensorArray
-
- TensorArray(BaseCudnnHelper.TensorArray) - Constructor for class org.deeplearning4j.nn.layers.BaseCudnnHelper.TensorArray
-
- TensorFlowCnnToFeedForwardPreProcessor - Class in org.deeplearning4j.nn.modelimport.keras.preprocessors
-
Specialized CnnToFeedForwardInputPreProcessor for use with
Convolutional layers imported from Keras using the TensorFlow
backend.
- TensorFlowCnnToFeedForwardPreProcessor(int, int, int) - Constructor for class org.deeplearning4j.nn.modelimport.keras.preprocessors.TensorFlowCnnToFeedForwardPreProcessor
-
- TensorFlowCnnToFeedForwardPreProcessor(int, int) - Constructor for class org.deeplearning4j.nn.modelimport.keras.preprocessors.TensorFlowCnnToFeedForwardPreProcessor
-
- TensorFlowCnnToFeedForwardPreProcessor() - Constructor for class org.deeplearning4j.nn.modelimport.keras.preprocessors.TensorFlowCnnToFeedForwardPreProcessor
-
- Term - Class in org.ansj.domain
-
- Term(String, int, AnsjItem) - Constructor for class org.ansj.domain.Term
-
- Term(String, int, TermNatures) - Constructor for class org.ansj.domain.Term
-
- Term(String, int, String, int) - Constructor for class org.ansj.domain.Term
-
- TermArrRecognition - Interface in org.ansj.recognition
-
词语识别接口,用来识别词语
- terminate(int, double) - Method in class org.deeplearning4j.earlystopping.termination.BestScoreEpochTerminationCondition
-
- terminate(int, double) - Method in interface org.deeplearning4j.earlystopping.termination.EpochTerminationCondition
-
Should the early stopping training terminate at this epoch, based on the calculated score and the epoch number?
Returns true if training should terminated, or false otherwise
- terminate(double) - Method in class org.deeplearning4j.earlystopping.termination.InvalidScoreIterationTerminationCondition
-
- terminate(double) - Method in interface org.deeplearning4j.earlystopping.termination.IterationTerminationCondition
-
Should early stopping training terminate at this iteration, based on the score for the last iteration?
return true if training should be terminated immediately, or false otherwise
- terminate(int, double) - Method in class org.deeplearning4j.earlystopping.termination.MaxEpochsTerminationCondition
-
- terminate(double) - Method in class org.deeplearning4j.earlystopping.termination.MaxScoreIterationTerminationCondition
-
- terminate(double) - Method in class org.deeplearning4j.earlystopping.termination.MaxTimeIterationTerminationCondition
-
- terminate(int, double) - Method in class org.deeplearning4j.earlystopping.termination.ScoreImprovementEpochTerminationCondition
-
- terminate(double, double, Object[]) - Method in interface org.deeplearning4j.optimize.api.TerminationCondition
-
Whether to terminate based on the given metadata
- terminate(double, double, Object[]) - Method in class org.deeplearning4j.optimize.terminations.EpsTermination
-
- terminate(double, double, Object[]) - Method in class org.deeplearning4j.optimize.terminations.Norm2Termination
-
- terminate(double, double, Object[]) - Method in class org.deeplearning4j.optimize.terminations.ZeroDirection
-
- terminateCluster() - Method in class org.deeplearning4j.aws.emr.SparkEMRClient
-
Terminates a cluster
- TERMINATING_CHARACTER - Static variable in class com.atilika.kuromoji.trie.DoubleArrayTrie
-
- terminationCondition - Variable in class org.deeplearning4j.clustering.strategy.BaseClusteringStrategy
-
- TerminationCondition - Interface in org.deeplearning4j.optimize.api
-
Created by agibsonccc on 12/24/14.
- terminationConditions - Variable in class org.deeplearning4j.optimize.solvers.BaseOptimizer
-
- TerminationConditions - Class in org.deeplearning4j.optimize.terminations
-
Created by agibsonccc on 12/24/14.
- TerminationConditions() - Constructor for class org.deeplearning4j.optimize.terminations.TerminationConditions
-
- terminationReason - Variable in class org.deeplearning4j.parallelism.EarlyStoppingParallelTrainer
-
- terminator - Variable in class org.deeplearning4j.datasets.iterator.AsyncDataSetIterator
-
- terminator - Variable in class org.deeplearning4j.datasets.iterator.AsyncMultiDataSetIterator
-
- terminator - Variable in class org.deeplearning4j.parallelism.AsyncIterator
-
- termLink(Term, Term) - Static method in class org.ansj.util.TermUtil
-
- TermNature - Class in org.ansj.domain
-
一个词里面会有一些词性
- TermNature(String, int) - Constructor for class org.ansj.domain.TermNature
-
- termNature - Variable in class org.ansj.recognition.impl.NatureRecognition.NatureTerm
-
- termNatures - Variable in class org.ansj.domain.AnsjItem
-
frequency : 词性词典,以及词性的相关权重
- termNatures() - Method in class org.ansj.domain.Term
-
获得这个term的所有词性
- TermNatures - Class in org.ansj.domain
-
每一个term都拥有一个词性集合
- TermNatures(TermNature[], int) - Constructor for class org.ansj.domain.TermNatures
-
构造方法.一个词对应这种玩意
- TermNatures(TermNature) - Constructor for class org.ansj.domain.TermNatures
-
- TermNatures(TermNature, int, int) - Constructor for class org.ansj.domain.TermNatures
-
- termNatures - Variable in class org.ansj.domain.TermNatures
-
关于这个term的所有词性
- terms - Variable in class org.ansj.util.Graph
-
- TermUtil - Class in org.ansj.util
-
term的操作类
- TermUtil() - Constructor for class org.ansj.util.TermUtil
-
- TermUtil.InsertTermType - Enum in org.ansj.util
-
- TEST_FILE_LABELS_FILENAME_UNZIPPED - Static variable in class org.deeplearning4j.base.MnistFetcher
-
- TEST_FILES_FILENAME_UNZIPPED - Static variable in class org.deeplearning4j.base.MnistFetcher
-
- TestDataSetIterator - Class in org.deeplearning4j.datasets.test
-
Track number of times the dataset iterator has been called
- TestDataSetIterator(DataSetIterator) - Constructor for class org.deeplearning4j.datasets.test.TestDataSetIterator
-
- TextGenerationLSTM - Class in org.deeplearning4j.zoo.model
-
LSTM designed for text generation.
- TextPipeline - Class in org.deeplearning4j.spark.text.functions
-
A spark based text pipeline
with minimum word frequency and stop words
- TextPipeline() - Constructor for class org.deeplearning4j.spark.text.functions.TextPipeline
-
- TextPipeline(JavaRDD<String>, Broadcast<Map<String, Object>>) - Constructor for class org.deeplearning4j.spark.text.functions.TextPipeline
-
- TextVectorizer - Interface in org.deeplearning4j.bagofwords.vectorizer
-
Vectorizes text
- tf(int, int) - Static method in class org.deeplearning4j.clustering.util.MathUtils
-
Term frequency: 1+ log10(count)
- tfidf(double, double) - Static method in class org.deeplearning4j.clustering.util.MathUtils
-
Return td * idf
- TfidfVectorizer - Class in org.deeplearning4j.bagofwords.vectorizer
-
- TfidfVectorizer() - Constructor for class org.deeplearning4j.bagofwords.vectorizer.TfidfVectorizer
-
- TfidfVectorizer.Builder - Class in org.deeplearning4j.bagofwords.vectorizer
-
- tfidfWord(String, long, long) - Method in class org.deeplearning4j.bagofwords.vectorizer.TfidfVectorizer
-
- theta(double) - Method in class org.deeplearning4j.plot.BarnesHutTsne.Builder
-
- thread - Variable in class org.deeplearning4j.datasets.iterator.AsyncDataSetIterator
-
- thread - Variable in class org.deeplearning4j.datasets.iterator.AsyncMultiDataSetIterator
-
- thread - Variable in class org.deeplearning4j.parallelism.AsyncIterator
-
- threadId(int) - Method in class org.deeplearning4j.parallelism.parameterserver.ParameterServerTrainer.ParameterServerTrainerBuilder
-
- threadId - Variable in class org.deeplearning4j.parallelism.trainer.DefaultTrainer
-
- threadId - Variable in class org.deeplearning4j.spark.stats.BaseEventStats
-
- threads - Variable in class org.deeplearning4j.models.sequencevectors.transformers.impl.iterables.ParallelTransformerIterator
-
- ThreadUtils - Class in org.deeplearning4j.util
-
Utils for the basic use and flow of threads.
- ThreadUtils() - Constructor for class org.deeplearning4j.util.ThreadUtils
-
- ThreadUtils.UncheckedInterruptedException - Exception in org.deeplearning4j.util
-
- threshold - Variable in class org.deeplearning4j.optimize.solvers.accumulation.EncodedGradientsAccumulator.Builder
-
- threshold - Variable in class org.deeplearning4j.optimize.solvers.accumulation.EncodingHandler
-
- threshold - Variable in class org.deeplearning4j.spark.parameterserver.conf.SharedTrainingConfiguration
-
- threshold - Variable in class org.deeplearning4j.spark.parameterserver.training.SharedTrainingMaster.Builder
-
- threshold - Variable in class org.deeplearning4j.spark.parameterserver.training.SharedTrainingMaster
-
- thresholdStep - Variable in class org.deeplearning4j.optimize.solvers.accumulation.EncodingHandler
-
- thresholdStep - Variable in class org.deeplearning4j.spark.parameterserver.conf.SharedTrainingConfiguration
-
- thresholdStep - Variable in class org.deeplearning4j.spark.parameterserver.training.SharedTrainingMaster.Builder
-
- thresholdStep(double) - Method in class org.deeplearning4j.spark.parameterserver.training.SharedTrainingMaster.Builder
-
Step size for threshold decay
Default value: 1e-5
- thresholdStep - Variable in class org.deeplearning4j.spark.parameterserver.training.SharedTrainingMaster
-
- throwable - Variable in class org.deeplearning4j.datasets.iterator.AsyncDataSetIterator
-
- throwable - Variable in class org.deeplearning4j.datasets.iterator.AsyncMultiDataSetIterator
-
- throwable - Variable in class org.deeplearning4j.optimize.solvers.accumulation.EncodedGradientsAccumulator
-
- thrownException(Exception) - Method in class org.deeplearning4j.parallelism.parameterserver.ParameterServerTrainer.ParameterServerTrainerBuilder
-
- thrownException - Variable in class org.deeplearning4j.parallelism.trainer.DefaultTrainer
-
- tick() - Method in class org.deeplearning4j.models.glove.count.RoundCount
-
- time() - Method in class org.deeplearning4j.ui.stats.sbe.StaticInfoDecoder
-
- time(long) - Method in class org.deeplearning4j.ui.stats.sbe.StaticInfoEncoder
-
- time() - Method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder
-
- time(long) - Method in class org.deeplearning4j.ui.stats.sbe.UpdateEncoder
-
- timeId() - Static method in class org.deeplearning4j.ui.stats.sbe.StaticInfoDecoder
-
- timeId() - Static method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder
-
- TimeIterationListener - Class in org.deeplearning4j.optimize.listeners
-
Time Iteration Listener.
- TimeIterationListener(int) - Constructor for class org.deeplearning4j.optimize.listeners.TimeIterationListener
-
Constructor
- TimelineEntry(String, long, long) - Constructor for class org.deeplearning4j.ui.components.chart.ChartTimeline.TimelineEntry
-
- TimelineEntry(String, long, long, Color) - Constructor for class org.deeplearning4j.ui.components.chart.ChartTimeline.TimelineEntry
-
- timeMaxValue() - Static method in class org.deeplearning4j.ui.stats.sbe.StaticInfoDecoder
-
- timeMaxValue() - Static method in class org.deeplearning4j.ui.stats.sbe.StaticInfoEncoder
-
- timeMaxValue() - Static method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder
-
- timeMaxValue() - Static method in class org.deeplearning4j.ui.stats.sbe.UpdateEncoder
-
- timeMetaAttribute(MetaAttribute) - Static method in class org.deeplearning4j.ui.stats.sbe.StaticInfoDecoder
-
- timeMetaAttribute(MetaAttribute) - Static method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder
-
- timeMinValue() - Static method in class org.deeplearning4j.ui.stats.sbe.StaticInfoDecoder
-
- timeMinValue() - Static method in class org.deeplearning4j.ui.stats.sbe.StaticInfoEncoder
-
- timeMinValue() - Static method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder
-
- timeMinValue() - Static method in class org.deeplearning4j.ui.stats.sbe.UpdateEncoder
-
- timeMode - Variable in class org.deeplearning4j.optimize.listeners.SleepyTrainingListener
-
- timeNullValue() - Static method in class org.deeplearning4j.ui.stats.sbe.StaticInfoDecoder
-
- timeNullValue() - Static method in class org.deeplearning4j.ui.stats.sbe.StaticInfoEncoder
-
- timeNullValue() - Static method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder
-
- timeNullValue() - Static method in class org.deeplearning4j.ui.stats.sbe.UpdateEncoder
-
- timerBP - Variable in class org.deeplearning4j.optimize.listeners.SleepyTrainingListener
-
- TimeRecognition - Class in org.ansj.recognition.impl
-
时间识别抽取
- TimeRecognition() - Constructor for class org.ansj.recognition.impl.TimeRecognition
-
- timerEE - Variable in class org.deeplearning4j.optimize.listeners.SleepyTrainingListener
-
- timerES - Variable in class org.deeplearning4j.optimize.listeners.SleepyTrainingListener
-
- timerFF - Variable in class org.deeplearning4j.optimize.listeners.SleepyTrainingListener
-
- timerIteration - Variable in class org.deeplearning4j.optimize.listeners.SleepyTrainingListener
-
- times(double[]) - Static method in class org.deeplearning4j.clustering.util.MathUtils
-
This returns the product of all numbers in the given array.
- timeSeriesRandomOffset(boolean, long) - Method in class org.deeplearning4j.datasets.datavec.RecordReaderMultiDataSetIterator.Builder
-
For use with timeseries trained with tbptt
In a given minbatch, shorter time series are padded and appropriately masked to be the same length as the longest time series.
- TimeSeriesUtils - Class in org.deeplearning4j.util
-
Basic time series utils
- TimeSource - Interface in org.deeplearning4j.spark.time
-
A time source is an abstraction of system time away from the local system clock.
- TIMESOURCE_CLASSNAME_PROPERTY - Static variable in class org.deeplearning4j.spark.time.TimeSourceProvider
-
Name of the system property to set if the TimeSource type/class is to be customized
- TimeSourceProvider - Class in org.deeplearning4j.spark.time
-
- timeStamp() - Method in class org.deeplearning4j.ui.stats.sbe.StorageMetaDataDecoder
-
- timeStamp(long) - Method in class org.deeplearning4j.ui.stats.sbe.StorageMetaDataEncoder
-
- timeStampId() - Static method in class org.deeplearning4j.ui.stats.sbe.StorageMetaDataDecoder
-
- timeStampMaxValue() - Static method in class org.deeplearning4j.ui.stats.sbe.StorageMetaDataDecoder
-
- timeStampMaxValue() - Static method in class org.deeplearning4j.ui.stats.sbe.StorageMetaDataEncoder
-
- timeStampMetaAttribute(MetaAttribute) - Static method in class org.deeplearning4j.ui.stats.sbe.StorageMetaDataDecoder
-
- timeStampMinValue() - Static method in class org.deeplearning4j.ui.stats.sbe.StorageMetaDataDecoder
-
- timeStampMinValue() - Static method in class org.deeplearning4j.ui.stats.sbe.StorageMetaDataEncoder
-
- timeStampNullValue() - Static method in class org.deeplearning4j.ui.stats.sbe.StorageMetaDataDecoder
-
- timeStampNullValue() - Static method in class org.deeplearning4j.ui.stats.sbe.StorageMetaDataEncoder
-
- TinyImageNetDataSetIterator - Class in org.deeplearning4j.datasets.iterator.impl
-
Tiny ImageNet is a subset of the ImageNet database.
- TinyImageNetDataSetIterator(int) - Constructor for class org.deeplearning4j.datasets.iterator.impl.TinyImageNetDataSetIterator
-
- TinyImageNetDataSetIterator(int, DataSetType) - Constructor for class org.deeplearning4j.datasets.iterator.impl.TinyImageNetDataSetIterator
-
- TinyImageNetDataSetIterator(int, int[], DataSetType, ImageTransform, long) - Constructor for class org.deeplearning4j.datasets.iterator.impl.TinyImageNetDataSetIterator
-
Get the Tiny ImageNet iterator with specified train/test set and custom transform.
- TinyImageNetFetcher - Class in org.deeplearning4j.datasets.fetchers
-
Tiny ImageNet is a subset of the ImageNet database.
- TinyImageNetFetcher() - Constructor for class org.deeplearning4j.datasets.fetchers.TinyImageNetFetcher
-
- TinyYOLO - Class in org.deeplearning4j.zoo.model
-
Tiny YOLO
Reference: https://arxiv.org/pdf/1612.08242.pdf
- title(String) - Method in class org.deeplearning4j.ui.components.decorator.DecoratorAccordion.Builder
-
- titleStyle - Variable in class org.deeplearning4j.ui.components.chart.style.StyleChart.Builder
-
- titleStyle(StyleText) - Method in class org.deeplearning4j.ui.components.chart.style.StyleChart.Builder
-
- titleStyle - Variable in class org.deeplearning4j.ui.components.chart.style.StyleChart
-
- to() - Method in class org.ansj.domain.Term
-
- ToAnalysis - Class in org.ansj.splitWord.analysis
-
标准分词
- ToAnalysis() - Constructor for class org.ansj.splitWord.analysis.ToAnalysis
-
- ToAnalysis(Reader) - Constructor for class org.ansj.splitWord.analysis.ToAnalysis
-
- toArray() - Method in class org.deeplearning4j.optimize.solvers.accumulation.FancyBlockingQueue
-
- toArray(T[]) - Method in class org.deeplearning4j.optimize.solvers.accumulation.FancyBlockingQueue
-
- toArray() - Method in class org.deeplearning4j.parallelism.ConcurrentHashSet
-
Deprecated.
- toArray(T[]) - Method in class org.deeplearning4j.parallelism.ConcurrentHashSet
-
Deprecated.
- toArray() - Method in class org.deeplearning4j.parallelism.MagicQueue
-
Deprecated.
This method isn't supported
- toArray(T[]) - Method in class org.deeplearning4j.parallelism.MagicQueue
-
Deprecated.
This method isn't supported
- toArray() - Method in class org.deeplearning4j.util.DiskBasedQueue
-
- toArray(T[]) - Method in class org.deeplearning4j.util.DiskBasedQueue
-
- toBitString(K) - Method in interface com.atilika.kuromoji.trie.PatriciaTrie.KeyMapper
-
Formats a key as a String
- toBitString(String) - Method in class com.atilika.kuromoji.trie.PatriciaTrie.StringKeyMapper
-
- toBytes(boolean, String) - Static method in class org.deeplearning4j.ui.stats.impl.SbeUtil
-
- toBytes(boolean, String[]) - Static method in class org.deeplearning4j.ui.stats.impl.SbeUtil
-
- toBytes(Map<String, String>) - Static method in class org.deeplearning4j.ui.stats.impl.SbeUtil
-
- toBytesSerializable(Serializable) - Static method in class org.deeplearning4j.ui.stats.impl.SbeUtil
-
- toClassifierPrediction(Vector) - Static method in class org.deeplearning4j.spark.util.MLLibUtil
-
This is for the edge case where
you have a single output layer
and need to convert the output layer to
an index
- toComputationGraph() - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
-
Convert this MultiLayerNetwork to a ComputationGraph
- toComputationGraph(MultiLayerNetwork) - Static method in class org.deeplearning4j.util.NetworkUtils
-
Convert a MultiLayerNetwork to a ComputationGraph
- toCSV() - Method in class org.deeplearning4j.eval.ConfusionMatrix
-
Outputs the ConfusionMatrix as comma-separated values for easy import into spreadsheets
- toDecimal(String) - Static method in class org.deeplearning4j.clustering.util.MathUtils
-
This will convert the given binary string to a decimal based
integer
- toEncodedJson() - Method in class org.deeplearning4j.models.embeddings.loader.VectorsConfiguration
-
- toFileString() - Method in class org.deeplearning4j.optimize.listeners.checkpoint.Checkpoint
-
- toHTML() - Method in class org.deeplearning4j.eval.ConfusionMatrix
-
Outputs Confusion Matrix in an HTML table.
- toInputMatrix(List<Window>, Word2Vec) - Static method in class org.deeplearning4j.text.movingwindow.WordConverter
-
- toInputMatrix() - Method in class org.deeplearning4j.text.movingwindow.WordConverter
-
- toJson() - Method in class org.deeplearning4j.eval.BaseEvaluation
-
- toJson() - Method in class org.deeplearning4j.eval.curves.BaseCurve
-
- toJson() - Method in class org.deeplearning4j.eval.curves.BaseHistogram
-
- toJson() - Method in interface org.deeplearning4j.eval.IEvaluation
-
- toJson() - Method in class org.deeplearning4j.models.embeddings.loader.VectorsConfiguration
-
- toJSON() - Method in class org.deeplearning4j.models.sequencevectors.sequence.SequenceElement
-
- toJSON() - Method in class org.deeplearning4j.models.sequencevectors.sequence.ShallowSequenceElement
-
- toJSON() - Method in class org.deeplearning4j.models.word2vec.VocabWord
-
- toJson() - Method in class org.deeplearning4j.models.word2vec.wordstore.VocabularyWord
-
- toJson() - Method in class org.deeplearning4j.nn.conf.ComputationGraphConfiguration
-
- toJson() - Method in class org.deeplearning4j.nn.conf.memory.MemoryReport
-
- toJson() - Method in class org.deeplearning4j.nn.conf.MultiLayerConfiguration
-
- toJson() - Method in class org.deeplearning4j.nn.conf.NeuralNetConfiguration
-
Return this configuration as json
- toJson() - Method in class org.deeplearning4j.nn.transferlearning.FineTuneConfiguration
-
- toJson() - Method in interface org.deeplearning4j.spark.api.TrainingMaster
-
Get the TrainingMaster configuration as JSON
- toJson() - Method in class org.deeplearning4j.spark.impl.paramavg.ParameterAveragingTrainingMaster
-
- toJson() - Method in class org.deeplearning4j.spark.parameterserver.training.SharedTrainingMaster
-
- Token - Class in com.atilika.kuromoji.ipadic
-
IPADIC token produced by the IPADIC tokenizer with various morphological features
- Token(int, String, ViterbiNode.Type, int, Dictionary) - Constructor for class com.atilika.kuromoji.ipadic.Token
-
- TOKEN_INFO_DICTIONARY_FILENAME - Static variable in class com.atilika.kuromoji.dict.TokenInfoDictionary
-
- TOKEN_PREPROCESSOR - Static variable in class org.deeplearning4j.spark.models.embeddings.word2vec.Word2VecVariables
-
Deprecated.
- TokenBase - Class in com.atilika.kuromoji
-
Abstract token class with features shared by all tokens produced by all tokenizers
- TokenBase(int, String, ViterbiNode.Type, int, Dictionary) - Constructor for class com.atilika.kuromoji.TokenBase
-
- tokenFactory - Variable in class com.atilika.kuromoji.TokenizerBase.Builder
-
- tokenFactory - Variable in class com.atilika.kuromoji.TokenizerBase
-
- TokenFactory<T extends TokenBase> - Interface in com.atilika.kuromoji.viterbi
-
- tokenFactory - Variable in class org.deeplearning4j.models.glove.Glove.Builder
-
- tokenFor(String) - Method in class org.deeplearning4j.models.word2vec.wordstore.inmemory.AbstractCache
-
Returns SequenceElement for specified label.
- tokenFor(long) - Method in class org.deeplearning4j.models.word2vec.wordstore.inmemory.AbstractCache
-
- tokenFor(String) - Method in class org.deeplearning4j.models.word2vec.wordstore.inmemory.InMemoryLookupCache
-
Deprecated.
- tokenFor(long) - Method in class org.deeplearning4j.models.word2vec.wordstore.inmemory.InMemoryLookupCache
-
Deprecated.
- tokenFor(String) - Method in interface org.deeplearning4j.models.word2vec.wordstore.VocabCache
-
Returns the token (again not necessarily in the vocab)
for this word
- tokenFor(long) - Method in interface org.deeplearning4j.models.word2vec.wordstore.VocabCache
-
- tokenInfo - Variable in class com.atilika.kuromoji.buffer.BufferEntry
-
- TokenInfoBuffer - Class in com.atilika.kuromoji.buffer
-
- TokenInfoBuffer(InputStream) - Constructor for class com.atilika.kuromoji.buffer.TokenInfoBuffer
-
- tokenInfoBuffer - Variable in class com.atilika.kuromoji.dict.TokenInfoDictionary
-
- TokenInfoBufferCompiler - Class in com.atilika.kuromoji.compile
-
- TokenInfoBufferCompiler(OutputStream, List<BufferEntry>) - Constructor for class com.atilika.kuromoji.compile.TokenInfoBufferCompiler
-
- TokenInfoDictionary - Class in com.atilika.kuromoji.dict
-
- TokenInfoDictionary() - Constructor for class com.atilika.kuromoji.dict.TokenInfoDictionary
-
- tokenInfoDictionary - Variable in class com.atilika.kuromoji.TokenizerBase.Builder
-
- TokenInfoDictionaryCompiler - Class in com.atilika.kuromoji.ipadic.compile
-
- TokenInfoDictionaryCompiler(String) - Constructor for class com.atilika.kuromoji.ipadic.compile.TokenInfoDictionaryCompiler
-
- TokenInfoDictionaryCompilerBase<T extends DictionaryEntryBase> - Class in com.atilika.kuromoji.compile
-
- TokenInfoDictionaryCompilerBase(String) - Constructor for class com.atilika.kuromoji.compile.TokenInfoDictionaryCompilerBase
-
- tokenInfos - Variable in class com.atilika.kuromoji.buffer.BufferEntry
-
- tokenize(String) - Method in class com.atilika.kuromoji.ipadic.Tokenizer
-
Tokenizes the provided text and returns a list of tokens with various feature information
- tokenize(String) - Method in class com.atilika.kuromoji.TokenizerBase
-
- tokenize(TokenizerFactory) - Method in class org.deeplearning4j.bagofwords.vectorizer.Builder
-
Deprecated.
- tokenize() - Method in class org.deeplearning4j.spark.text.functions.TextPipeline
-
- tokenize(CAS, AnnotationFS) - Method in class org.deeplearning4j.text.tokenization.tokenizer.ConcurrentTokenizer
-
- Tokenizer - Class in com.atilika.kuromoji.ipadic
-
A tokenizer based on the IPADIC dictionary
- Tokenizer() - Constructor for class com.atilika.kuromoji.ipadic.Tokenizer
-
Construct a default tokenizer
- TOKENIZER - Static variable in class org.deeplearning4j.spark.models.embeddings.word2vec.Word2VecVariables
-
Deprecated.
- Tokenizer - Interface in org.deeplearning4j.text.tokenization.tokenizer
-
A representation of a tokenizer.
- Tokenizer.Builder - Class in com.atilika.kuromoji.ipadic
-
Builder class for creating a customized tokenizer instance
- TokenizerAnnotator - Class in org.deeplearning4j.text.annotator
-
Overrides OpenNLP tokenizer to be thread safe
- TokenizerAnnotator() - Constructor for class org.deeplearning4j.text.annotator.TokenizerAnnotator
-
- TokenizerBase - Class in com.atilika.kuromoji
-
TokenizerBase main class
- TokenizerBase() - Constructor for class com.atilika.kuromoji.TokenizerBase
-
- TokenizerBase.Builder - Class in com.atilika.kuromoji
-
Abstract Builder shared by all tokenizers
- TokenizerBase.Mode - Enum in com.atilika.kuromoji
-
- tokenizerFactory - Variable in class org.deeplearning4j.bagofwords.vectorizer.BagOfWordsVectorizer.Builder
-
- tokenizerFactory - Variable in class org.deeplearning4j.bagofwords.vectorizer.BaseTextVectorizer
-
- tokenizerFactory - Variable in class org.deeplearning4j.bagofwords.vectorizer.Builder
-
Deprecated.
- tokenizerFactory - Variable in class org.deeplearning4j.bagofwords.vectorizer.TfidfVectorizer.Builder
-
- tokenizerFactory(TokenizerFactory) - Method in class org.deeplearning4j.iterator.CnnSentenceDataSetIterator.Builder
-
- tokenizerFactory(TokenizerFactory) - Method in class org.deeplearning4j.models.glove.Glove.Builder
-
Sets TokenizerFactory to be used for training
- tokenizerFactory(TokenizerFactory) - Method in class org.deeplearning4j.models.paragraphvectors.ParagraphVectors.Builder
-
This method defines TokenizerFactory to be used for strings tokenization during training
PLEASE NOTE: If external VocabCache is used, the same TokenizerFactory should be used to keep derived tokens equal.
- tokenizerFactory - Variable in class org.deeplearning4j.models.sequencevectors.transformers.impl.SentenceTransformer.Builder
-
- tokenizerFactory(TokenizerFactory) - Method in class org.deeplearning4j.models.sequencevectors.transformers.impl.SentenceTransformer.Builder
-
- tokenizerFactory - Variable in class org.deeplearning4j.models.sequencevectors.transformers.impl.SentenceTransformer
-
- tokenizerFactory - Variable in class org.deeplearning4j.models.word2vec.Word2Vec.Builder
-
- tokenizerFactory(TokenizerFactory) - Method in class org.deeplearning4j.models.word2vec.Word2Vec.Builder
-
This method defines TokenizerFactory to be used for strings tokenization during training
PLEASE NOTE: If external VocabCache is used, the same TokenizerFactory should be used to keep derived tokens equal.
- tokenizerFactory - Variable in class org.deeplearning4j.models.word2vec.Word2Vec
-
- tokenizerFactory - Variable in class org.deeplearning4j.spark.models.embeddings.word2vec.Word2Vec.Builder
-
- tokenizerFactory(TokenizerFactory) - Method in class org.deeplearning4j.spark.models.embeddings.word2vec.Word2Vec.Builder
-
Specifies TokenizerFactory to be used for tokenization
PLEASE NOTE: You can't use anonymous implementation here
- tokenizerFactory(String) - Method in class org.deeplearning4j.spark.models.embeddings.word2vec.Word2Vec.Builder
-
Specifies TokenizerFactory class to be used for tokenization
- tokenizerFactory - Variable in class org.deeplearning4j.spark.models.sequencevectors.functions.BaseTokenizerFunction
-
- TokenizerFactory - Interface in org.deeplearning4j.text.tokenization.tokenizerfactory
-
Generates a tokenizer for a given string
- TokenizerFunction - Class in org.deeplearning4j.spark.models.sequencevectors.functions
-
- TokenizerFunction(Broadcast<VectorsConfiguration>) - Constructor for class org.deeplearning4j.spark.models.sequencevectors.functions.TokenizerFunction
-
- TokenizerFunction - Class in org.deeplearning4j.spark.text.functions
-
Tokenizer function
- TokenizerFunction(String, String, int) - Constructor for class org.deeplearning4j.spark.text.functions.TokenizerFunction
-
- TokenPreProcess - Interface in org.deeplearning4j.text.tokenization.tokenizer
-
Token preprocessing
- tokenPreprocessor(String) - Method in class org.deeplearning4j.spark.models.embeddings.word2vec.Word2Vec.Builder
-
Specifies TokenPreProcessor class to be used during tokenization
- tokenPreprocessor - Variable in class org.deeplearning4j.spark.models.sequencevectors.functions.BaseTokenizerFunction
-
- tokens() - Method in class org.deeplearning4j.models.word2vec.wordstore.inmemory.AbstractCache
-
Returns collection of SequenceElements from this vocabulary.
- tokens - Variable in class org.deeplearning4j.models.word2vec.wordstore.inmemory.InMemoryLookupCache
-
Deprecated.
- tokens() - Method in class org.deeplearning4j.models.word2vec.wordstore.inmemory.InMemoryLookupCache
-
Deprecated.
- tokens() - Method in interface org.deeplearning4j.models.word2vec.wordstore.VocabCache
-
All of the tokens in the cache, (not necessarily apart of the vocab)
- toLabelMatrix(List<String>, List<Window>) - Static method in class org.deeplearning4j.text.movingwindow.WordConverter
-
- toLabelMatrix(List<String>) - Method in class org.deeplearning4j.text.movingwindow.WordConverter
-
- tolerance(double) - Method in class org.deeplearning4j.plot.BarnesHutTsne.Builder
-
- tolerance - Variable in class org.deeplearning4j.plot.BarnesHutTsne
-
- tolerance - Variable in class org.deeplearning4j.plot.Tsne.Builder
-
- tolerance(double) - Method in class org.deeplearning4j.plot.Tsne.Builder
-
- tolerance - Variable in class org.deeplearning4j.plot.Tsne
-
- toMatrix(Matrix) - Static method in class org.deeplearning4j.spark.util.MLLibUtil
-
Convert an ndarray to a matrix.
- toMatrix(INDArray) - Static method in class org.deeplearning4j.spark.util.MLLibUtil
-
Convert an ndarray to a matrix.
- toMultiDataSet(DataSet) - Static method in class org.deeplearning4j.nn.graph.util.ComputationGraphUtil
-
Convert a DataSet to the equivalent MultiDataSet
- toMultiDataSetIterator(DataSetIterator) - Static method in class org.deeplearning4j.nn.graph.util.ComputationGraphUtil
-
Convert a DataSetIterator to a MultiDataSetIterator, via an adaptor class
- topicName(String) - Method in class org.deeplearning4j.streaming.routes.CamelKafkaRouteBuilder.Builder
-
- topN - Variable in class org.deeplearning4j.eval.Evaluation
-
- topNAccuracy() - Method in class org.deeplearning4j.eval.Evaluation
-
Top N accuracy of the predictions so far.
- topNCorrectCount - Variable in class org.deeplearning4j.eval.Evaluation
-
- topNTotalCount - Variable in class org.deeplearning4j.eval.Evaluation
-
- toPoints(INDArray) - Static method in class org.deeplearning4j.clustering.cluster.Point
-
- toPoints(List<INDArray>) - Static method in class org.deeplearning4j.clustering.cluster.Point
-
- topologicalOrder - Variable in class org.deeplearning4j.nn.conf.ComputationGraphConfiguration
-
- topologicalOrder - Variable in class org.deeplearning4j.nn.graph.ComputationGraph
-
Indexes of graph vertices, in topological order.
- topologicalOrderStr - Variable in class org.deeplearning4j.nn.conf.ComputationGraphConfiguration
-
- topologicalSortOrder() - Method in class org.deeplearning4j.nn.graph.ComputationGraph
-
Calculate a topological sort order for the vertices in the graph.
- toPoolingType() - Method in enum org.deeplearning4j.nn.conf.layers.Subsampling3DLayer.PoolingType
-
- toPoolingType() - Method in enum org.deeplearning4j.nn.conf.layers.SubsamplingLayer.PoolingType
-
- toResponse(Throwable) - Method in class org.deeplearning4j.ui.exception.GenericExceptionMapper
-
- toResponse(JsonProcessingException) - Method in class org.deeplearning4j.ui.exception.JsonExceptionMapper
-
- toSentenceList(char[]) - Method in class org.ansj.app.summary.SummaryComputer
-
- toStream(String) - Method in class org.ansj.dic.impl.File2Stream
-
- toStream(String) - Method in class org.ansj.dic.impl.Jar2Stream
-
- toStream(String) - Method in class org.ansj.dic.impl.Jdbc2Stream
-
- toStream(String) - Method in class org.ansj.dic.impl.Url2Stream
-
- toStream(String) - Method in class org.ansj.dic.PathToStream
-
- toString() - Method in class com.atilika.kuromoji.buffer.FeatureInfoMap
-
- toString() - Method in class com.atilika.kuromoji.TokenBase
-
- toString() - Method in class com.atilika.kuromoji.trie.PatriciaTrie.PatriciaNode
- toString() - Method in class org.ansj.app.crf.pojo.Element
-
- toString() - Method in class org.ansj.app.keyword.Keyword
-
- toString() - Method in class org.ansj.app.summary.SummaryComputer.Sentence
-
- toString() - Method in class org.ansj.domain.Nature
-
- toString() - Method in class org.ansj.domain.NewWord
-
- toString() - Method in class org.ansj.domain.PersonNatureAttr
-
- toString() - Method in class org.ansj.domain.Result
-
- toString(String) - Method in class org.ansj.domain.Result
-
- toString() - Method in class org.ansj.domain.Term
-
- toString() - Method in class org.ansj.domain.TermNature
-
- toString() - Method in class org.ansj.recognition.impl.NatureRecognition.NatureTerm
-
- toString() - Method in class org.deeplearning4j.earlystopping.EarlyStoppingResult
-
- toString() - Method in class org.deeplearning4j.earlystopping.saver.InMemoryModelSaver
-
- toString() - Method in class org.deeplearning4j.earlystopping.saver.LocalFileGraphSaver
-
- toString() - Method in class org.deeplearning4j.earlystopping.saver.LocalFileModelSaver
-
- toString() - Method in class org.deeplearning4j.earlystopping.scorecalc.DataSetLossCalculator
-
- toString() - Method in class org.deeplearning4j.earlystopping.scorecalc.DataSetLossCalculatorCG
-
Deprecated.
- toString() - Method in class org.deeplearning4j.earlystopping.termination.BestScoreEpochTerminationCondition
-
- toString() - Method in class org.deeplearning4j.earlystopping.termination.InvalidScoreIterationTerminationCondition
-
- toString() - Method in class org.deeplearning4j.earlystopping.termination.MaxEpochsTerminationCondition
-
- toString() - Method in class org.deeplearning4j.earlystopping.termination.MaxScoreIterationTerminationCondition
-
- toString() - Method in class org.deeplearning4j.earlystopping.termination.MaxTimeIterationTerminationCondition
-
- toString() - Method in class org.deeplearning4j.earlystopping.termination.ScoreImprovementEpochTerminationCondition
-
- toString() - Method in class org.deeplearning4j.eval.BaseEvaluation
-
- toString() - Method in class org.deeplearning4j.eval.ConfusionMatrix
-
- toString() - Method in class org.deeplearning4j.eval.meta.Prediction
-
- toString() - Method in class org.deeplearning4j.graph.api.Edge
-
- toString() - Method in class org.deeplearning4j.graph.api.Vertex
-
- toString() - Method in class org.deeplearning4j.graph.graph.Graph
-
- toString() - Method in class org.deeplearning4j.models.embeddings.inmemory.InMemoryLookupTable
-
- toString() - Method in class org.deeplearning4j.models.sequencevectors.graph.primitives.Edge
-
- toString() - Method in class org.deeplearning4j.models.sequencevectors.graph.primitives.Graph
-
- toString() - Method in class org.deeplearning4j.models.sequencevectors.graph.primitives.Vertex
-
- toString() - Method in class org.deeplearning4j.models.sequencevectors.sequence.SequenceElement
-
- toString() - Method in class org.deeplearning4j.models.word2vec.VocabWord
-
- toString() - Method in class org.deeplearning4j.models.word2vec.wordstore.inmemory.InMemoryLookupCache
-
Deprecated.
- toString() - Method in class org.deeplearning4j.nn.conf.ComputationGraphConfiguration
-
- toString() - Method in class org.deeplearning4j.nn.conf.distribution.BinomialDistribution
-
- toString() - Method in class org.deeplearning4j.nn.conf.distribution.ConstantDistribution
-
- toString() - Method in class org.deeplearning4j.nn.conf.distribution.LogNormalDistribution
-
- toString() - Method in class org.deeplearning4j.nn.conf.distribution.NormalDistribution
-
- toString() - Method in class org.deeplearning4j.nn.conf.distribution.OrthogonalDistribution
-
- toString() - Method in class org.deeplearning4j.nn.conf.distribution.TruncatedNormalDistribution
-
- toString() - Method in class org.deeplearning4j.nn.conf.distribution.UniformDistribution
-
- toString() - Method in class org.deeplearning4j.nn.conf.graph.MergeVertex
-
- toString() - Method in class org.deeplearning4j.nn.conf.graph.rnn.LastTimeStepVertex
-
- toString() - Method in class org.deeplearning4j.nn.conf.graph.rnn.ReverseTimeSeriesVertex
-
- toString() - Method in class org.deeplearning4j.nn.conf.graph.StackVertex
-
- toString() - Method in class org.deeplearning4j.nn.conf.inputs.InputType.InputTypeConvolutional
-
- toString() - Method in class org.deeplearning4j.nn.conf.inputs.InputType.InputTypeConvolutional3D
-
- toString() - Method in class org.deeplearning4j.nn.conf.inputs.InputType.InputTypeConvolutionalFlat
-
- toString() - Method in class org.deeplearning4j.nn.conf.inputs.InputType.InputTypeFeedForward
-
- toString() - Method in class org.deeplearning4j.nn.conf.inputs.InputType.InputTypeRecurrent
-
- toString() - Method in class org.deeplearning4j.nn.conf.inputs.InputType
-
- toString() - Method in class org.deeplearning4j.nn.conf.layers.util.MaskLayer
-
- toString() - Method in class org.deeplearning4j.nn.conf.layers.util.MaskZeroLayer
-
- toString() - Method in class org.deeplearning4j.nn.conf.layers.variational.BernoulliReconstructionDistribution
-
- toString() - Method in class org.deeplearning4j.nn.conf.layers.variational.ExponentialReconstructionDistribution
-
- toString() - Method in class org.deeplearning4j.nn.conf.layers.variational.GaussianReconstructionDistribution
-
- toString() - Method in class org.deeplearning4j.nn.conf.layers.variational.LossFunctionWrapper
-
- toString() - Method in class org.deeplearning4j.nn.conf.memory.LayerMemoryReport
-
- toString() - Method in class org.deeplearning4j.nn.conf.memory.MemoryReport
-
- toString() - Method in class org.deeplearning4j.nn.conf.memory.NetworkMemoryReport
-
- toString() - Method in class org.deeplearning4j.nn.conf.MultiLayerConfiguration
-
- toString() - Method in class org.deeplearning4j.nn.conf.stepfunctions.DefaultStepFunction
-
- toString() - Method in class org.deeplearning4j.nn.conf.stepfunctions.GradientStepFunction
-
- toString() - Method in class org.deeplearning4j.nn.conf.stepfunctions.NegativeDefaultStepFunction
-
- toString() - Method in class org.deeplearning4j.nn.conf.stepfunctions.NegativeGradientStepFunction
-
- toString() - Method in class org.deeplearning4j.nn.gradient.DefaultGradient
-
- toString() - Method in class org.deeplearning4j.nn.graph.vertex.BaseGraphVertex
-
- toString() - Method in class org.deeplearning4j.nn.graph.vertex.impl.ElementWiseVertex
-
- toString() - Method in class org.deeplearning4j.nn.graph.vertex.impl.InputVertex
-
- toString() - Method in class org.deeplearning4j.nn.graph.vertex.impl.L2NormalizeVertex
-
- toString() - Method in class org.deeplearning4j.nn.graph.vertex.impl.L2Vertex
-
- toString() - Method in class org.deeplearning4j.nn.graph.vertex.impl.LayerVertex
-
- toString() - Method in class org.deeplearning4j.nn.graph.vertex.impl.MergeVertex
-
- toString() - Method in class org.deeplearning4j.nn.graph.vertex.impl.PoolHelperVertex
-
- toString() - Method in class org.deeplearning4j.nn.graph.vertex.impl.PreprocessorVertex
-
- toString() - Method in class org.deeplearning4j.nn.graph.vertex.impl.ReshapeVertex
-
- toString() - Method in class org.deeplearning4j.nn.graph.vertex.impl.rnn.DuplicateToTimeSeriesVertex
-
- toString() - Method in class org.deeplearning4j.nn.graph.vertex.impl.rnn.LastTimeStepVertex
-
- toString() - Method in class org.deeplearning4j.nn.graph.vertex.impl.rnn.ReverseTimeSeriesVertex
-
- toString() - Method in class org.deeplearning4j.nn.graph.vertex.impl.ScaleVertex
-
- toString() - Method in class org.deeplearning4j.nn.graph.vertex.impl.ShiftVertex
-
- toString() - Method in class org.deeplearning4j.nn.graph.vertex.impl.StackVertex
-
- toString() - Method in class org.deeplearning4j.nn.graph.vertex.impl.SubsetVertex
-
- toString() - Method in class org.deeplearning4j.nn.graph.vertex.impl.UnstackVertex
-
- toString() - Method in class org.deeplearning4j.nn.graph.vertex.VertexIndices
-
- toString() - Method in class org.deeplearning4j.nn.layers.BaseLayer
-
- toString() - Method in class org.deeplearning4j.nn.layers.feedforward.autoencoder.recursive.Tree
-
- toString() - Method in class org.deeplearning4j.nn.layers.objdetect.DetectedObject
-
- toString() - Method in class org.deeplearning4j.nn.transferlearning.FineTuneConfiguration.Builder
-
- toString() - Method in class org.deeplearning4j.spark.models.embeddings.glove.GloveChange
-
- toString() - Method in class org.deeplearning4j.spark.models.sequencevectors.export.ExportContainer
-
- toString() - Method in class org.deeplearning4j.text.movingwindow.Window
-
- toString() - Method in class org.deeplearning4j.ui.components.chart.ChartHistogram
-
- toString() - Method in class org.deeplearning4j.ui.components.chart.ChartHorizontalBar
-
- toString() - Method in class org.deeplearning4j.ui.components.chart.ChartLine
-
- toString() - Method in class org.deeplearning4j.ui.components.chart.ChartScatter
-
- toString() - Method in class org.deeplearning4j.ui.components.chart.ChartStackedArea
-
- toString() - Method in class org.deeplearning4j.ui.components.text.ComponentText
-
- toString() - Method in class org.deeplearning4j.ui.stats.sbe.GroupSizeEncodingDecoder
-
- toString() - Method in class org.deeplearning4j.ui.stats.sbe.GroupSizeEncodingEncoder
-
- toString() - Method in class org.deeplearning4j.ui.stats.sbe.InitFieldsPresentDecoder
-
- toString() - Method in class org.deeplearning4j.ui.stats.sbe.StaticInfoDecoder.HwDeviceInfoGroupDecoder
-
- toString() - Method in class org.deeplearning4j.ui.stats.sbe.StaticInfoDecoder.ModelParamNamesDecoder
-
- toString() - Method in class org.deeplearning4j.ui.stats.sbe.StaticInfoDecoder.SwEnvironmentInfoDecoder
-
- toString() - Method in class org.deeplearning4j.ui.stats.sbe.StaticInfoDecoder
-
- toString() - Method in class org.deeplearning4j.ui.stats.sbe.StaticInfoEncoder
-
- toString() - Method in class org.deeplearning4j.ui.stats.sbe.StorageMetaDataDecoder.ExtraMetaDataBytesDecoder
-
- toString() - Method in class org.deeplearning4j.ui.stats.sbe.StorageMetaDataDecoder
-
- toString() - Method in class org.deeplearning4j.ui.stats.sbe.StorageMetaDataEncoder
-
- toString() - Method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder.DataSetMetaDataBytesDecoder.MetaDataBytesDecoder
-
- toString() - Method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder.DataSetMetaDataBytesDecoder
-
- toString() - Method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder.GcStatsDecoder
-
- toString() - Method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder.LayerNamesDecoder
-
- toString() - Method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder.MemoryUseDecoder
-
- toString() - Method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder.ParamNamesDecoder
-
- toString() - Method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder.PerformanceDecoder
-
- toString() - Method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder.PerParameterStatsDecoder.HistogramsDecoder.HistogramCountsDecoder
-
- toString() - Method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder.PerParameterStatsDecoder.HistogramsDecoder
-
- toString() - Method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder.PerParameterStatsDecoder.SummaryStatDecoder
-
- toString() - Method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder.PerParameterStatsDecoder
-
- toString() - Method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder
-
- toString() - Method in class org.deeplearning4j.ui.stats.sbe.UpdateEncoder
-
- toString() - Method in class org.deeplearning4j.ui.stats.sbe.UpdateFieldsPresentDecoder
-
- toString() - Method in class org.deeplearning4j.ui.stats.sbe.VarDataUTF8Decoder
-
- toString() - Method in class org.deeplearning4j.ui.stats.sbe.VarDataUTF8Encoder
-
- toString() - Method in class org.deeplearning4j.ui.storage.BaseCollectionStatsStorage.SessionTypeId
-
- toString() - Method in class org.deeplearning4j.ui.storage.BaseCollectionStatsStorage.SessionTypeWorkerId
-
- toString() - Method in class org.deeplearning4j.ui.storage.FileStatsStorage
-
- toString() - Method in class org.deeplearning4j.ui.storage.InMemoryStatsStorage
-
- toString() - Method in class org.deeplearning4j.ui.storage.sqlite.J7FileStatsStorage
-
- toString() - Method in class org.deeplearning4j.zoo.util.ClassPrediction
-
- toStringWithOutNature() - Method in class org.ansj.domain.Result
-
返回没有词性的切分结果
- toStringWithOutNature(String) - Method in class org.ansj.domain.Result
-
返回没有词性的切分结果
- toSummary() - Method in class org.ansj.app.summary.SummaryComputer
-
计算摘要，利用关键词抽取计算
- toSummary(String) - Method in class org.ansj.app.summary.SummaryComputer
-
根据用户查询串计算摘要
- toSummary(List<Keyword>) - Method in class org.ansj.app.summary.SummaryComputer
-
计算摘要，传入用户自己算好的关键词
- TOTAL_FEATURES - Static variable in class com.atilika.kuromoji.ipadic.compile.DictionaryEntry
-
- totalCount(int) - Method in class org.deeplearning4j.eval.EvaluationBinary
-
Get the total number of values for the specified column, accounting for any masking
- totalExamples() - Method in class org.deeplearning4j.datasets.datavec.RecordReaderDataSetIterator
-
- totalExamples() - Method in class org.deeplearning4j.datasets.datavec.SequenceRecordReaderDataSetIterator
-
- totalExamples() - Method in class org.deeplearning4j.datasets.iterator.AbstractDataSetIterator
-
Total examples in the iterator
- totalExamples() - Method in class org.deeplearning4j.datasets.iterator.AsyncDataSetIterator
-
Total examples in the iterator
- totalExamples() - Method in class org.deeplearning4j.datasets.iterator.AsyncShieldDataSetIterator
-
Total examples in the iterator
- totalExamples() - Method in class org.deeplearning4j.datasets.iterator.BaseDatasetIterator
-
- totalExamples() - Method in interface org.deeplearning4j.datasets.iterator.DataSetFetcher
-
Deprecated.
The total number of examples
- totalExamples - Variable in class org.deeplearning4j.datasets.iterator.DataSetIteratorSplitter
-
- totalExamples() - Method in class org.deeplearning4j.datasets.iterator.EarlyTerminationDataSetIterator
-
- totalExamples() - Method in class org.deeplearning4j.datasets.iterator.ExistingDataSetIterator
-
- totalExamples() - Method in class org.deeplearning4j.datasets.iterator.file.FileDataSetIterator
-
- totalExamples() - Method in class org.deeplearning4j.datasets.iterator.FileSplitDataSetIterator
-
- totalExamples() - Method in class org.deeplearning4j.datasets.iterator.impl.BenchmarkDataSetIterator
-
- totalExamples() - Method in class org.deeplearning4j.datasets.iterator.impl.CifarDataSetIterator
-
- totalExamples() - Method in class org.deeplearning4j.datasets.iterator.impl.ListDataSetIterator
-
- totalExamples() - Method in class org.deeplearning4j.datasets.iterator.IteratorDataSetIterator
-
- totalExamples - Variable in class org.deeplearning4j.datasets.iterator.MultiDataSetIteratorSplitter
-
- totalExamples() - Method in class org.deeplearning4j.datasets.iterator.MultiDataSetWrapperIterator
-
- totalExamples() - Method in class org.deeplearning4j.datasets.iterator.MultipleEpochsIterator
-
Deprecated.
Total examples in the iterator
- totalExamples() - Method in class org.deeplearning4j.datasets.iterator.parallel.BaseParallelDataSetIterator
-
- totalExamples() - Method in class org.deeplearning4j.datasets.iterator.ReconstructionDataSetIterator
-
Total examples in the iterator
- totalExamples() - Method in class org.deeplearning4j.datasets.iterator.SamplingDataSetIterator
-
- totalExamples() - Method in class org.deeplearning4j.datasets.iterator.WorkspacesShieldDataSetIterator
-
- totalExamples() - Method in class org.deeplearning4j.datasets.test.TestDataSetIterator
-
- totalExamples() - Method in class org.deeplearning4j.iterator.CnnSentenceDataSetIterator
-
- totalExamples() - Method in class org.deeplearning4j.models.word2vec.iterator.Word2VecDataFetcher
-
- totalExamples() - Method in class org.deeplearning4j.models.word2vec.iterator.Word2VecDataSetIterator
-
- totalExamples() - Method in class org.deeplearning4j.spark.iterator.BaseDataSetIterator
-
- totalExamples() - Method in class org.deeplearning4j.spark.iterator.PathSparkDataSetIterator
-
- totalExamples() - Method in class org.deeplearning4j.spark.iterator.PortableDataStreamDataSetIterator
-
- totalExamples() - Method in class org.deeplearning4j.spark.parameterserver.iterators.VirtualDataSetIterator
-
- totalExamples() - Method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder.PerformanceDecoder
-
- totalExamples(long) - Method in class org.deeplearning4j.ui.stats.sbe.UpdateEncoder.PerformanceEncoder
-
- totalExamplesId() - Static method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder.PerformanceDecoder
-
- totalExamplesMaxValue() - Static method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder.PerformanceDecoder
-
- totalExamplesMaxValue() - Static method in class org.deeplearning4j.ui.stats.sbe.UpdateEncoder.PerformanceEncoder
-
- totalExamplesMetaAttribute(MetaAttribute) - Static method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder.PerformanceDecoder
-
- totalExamplesMinValue() - Static method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder.PerformanceDecoder
-
- totalExamplesMinValue() - Static method in class org.deeplearning4j.ui.stats.sbe.UpdateEncoder.PerformanceEncoder
-
- totalExamplesNullValue() - Static method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder.PerformanceDecoder
-
- totalExamplesNullValue() - Static method in class org.deeplearning4j.ui.stats.sbe.UpdateEncoder.PerformanceEncoder
-
- totalFeatures - Variable in class com.atilika.kuromoji.TokenizerBase.Builder
-
- totalIterations - Variable in class org.deeplearning4j.datasets.iterator.MultipleEpochsIterator
-
Deprecated.
- totalMinibatches() - Method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder.PerformanceDecoder
-
- totalMinibatches(long) - Method in class org.deeplearning4j.ui.stats.sbe.UpdateEncoder.PerformanceEncoder
-
- totalMinibatchesId() - Static method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder.PerformanceDecoder
-
- totalMinibatchesMaxValue() - Static method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder.PerformanceDecoder
-
- totalMinibatchesMaxValue() - Static method in class org.deeplearning4j.ui.stats.sbe.UpdateEncoder.PerformanceEncoder
-
- totalMinibatchesMetaAttribute(MetaAttribute) - Static method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder.PerformanceDecoder
-
- totalMinibatchesMinValue() - Static method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder.PerformanceDecoder
-
- totalMinibatchesMinValue() - Static method in class org.deeplearning4j.ui.stats.sbe.UpdateEncoder.PerformanceEncoder
-
- totalMinibatchesNullValue() - Static method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder.PerformanceDecoder
-
- totalMinibatchesNullValue() - Static method in class org.deeplearning4j.ui.stats.sbe.UpdateEncoder.PerformanceEncoder
-
- totalNumberOfDocs() - Method in class org.deeplearning4j.models.word2vec.wordstore.inmemory.AbstractCache
-
Returns total number of documents observed (if applicable)
- totalNumberOfDocs() - Method in class org.deeplearning4j.models.word2vec.wordstore.inmemory.InMemoryLookupCache
-
Deprecated.
- totalNumberOfDocs() - Method in interface org.deeplearning4j.models.word2vec.wordstore.VocabCache
-
Returns the total of number of documents encountered in the corpus
- totalNumSentences() - Method in interface org.deeplearning4j.iterator.LabeledSentenceProvider
-
Return the total number of sentences, or -1 if not available
- totalNumSentences() - Method in class org.deeplearning4j.iterator.provider.CollectionLabeledSentenceProvider
-
- totalNumSentences() - Method in class org.deeplearning4j.iterator.provider.FileLabeledSentenceProvider
-
- totalNumSentences() - Method in class org.deeplearning4j.iterator.provider.LabelAwareConverter
-
- totalOutcomes() - Method in class org.deeplearning4j.datasets.datavec.RecordReaderDataSetIterator
-
- totalOutcomes() - Method in class org.deeplearning4j.datasets.datavec.SequenceRecordReaderDataSetIterator
-
- totalOutcomes() - Method in class org.deeplearning4j.datasets.iterator.AbstractDataSetIterator
-
The number of labels for the dataset
- totalOutcomes() - Method in class org.deeplearning4j.datasets.iterator.AsyncDataSetIterator
-
The number of labels for the dataset
- totalOutcomes() - Method in class org.deeplearning4j.datasets.iterator.AsyncShieldDataSetIterator
-
The number of labels for the dataset
- totalOutcomes() - Method in class org.deeplearning4j.datasets.iterator.BaseDatasetIterator
-
- totalOutcomes() - Method in interface org.deeplearning4j.datasets.iterator.DataSetFetcher
-
Deprecated.
The number of labels for a dataset
- totalOutcomes() - Method in class org.deeplearning4j.datasets.iterator.EarlyTerminationDataSetIterator
-
- totalOutcomes() - Method in class org.deeplearning4j.datasets.iterator.ExistingDataSetIterator
-
- totalOutcomes() - Method in class org.deeplearning4j.datasets.iterator.file.FileDataSetIterator
-
- totalOutcomes() - Method in class org.deeplearning4j.datasets.iterator.FileSplitDataSetIterator
-
- totalOutcomes() - Method in class org.deeplearning4j.datasets.iterator.impl.BenchmarkDataSetIterator
-
- totalOutcomes() - Method in class org.deeplearning4j.datasets.iterator.impl.ListDataSetIterator
-
- totalOutcomes() - Method in class org.deeplearning4j.datasets.iterator.IteratorDataSetIterator
-
- totalOutcomes() - Method in class org.deeplearning4j.datasets.iterator.MultiDataSetWrapperIterator
-
- totalOutcomes() - Method in class org.deeplearning4j.datasets.iterator.MultipleEpochsIterator
-
Deprecated.
The number of labels for the dataset
- totalOutcomes() - Method in class org.deeplearning4j.datasets.iterator.parallel.BaseParallelDataSetIterator
-
- totalOutcomes() - Method in class org.deeplearning4j.datasets.iterator.ReconstructionDataSetIterator
-
The number of labels for the dataset
- totalOutcomes() - Method in class org.deeplearning4j.datasets.iterator.SamplingDataSetIterator
-
- totalOutcomes() - Method in class org.deeplearning4j.datasets.iterator.WorkspacesShieldDataSetIterator
-
- totalOutcomes() - Method in class org.deeplearning4j.datasets.test.TestDataSetIterator
-
- totalOutcomes() - Method in class org.deeplearning4j.iterator.CnnSentenceDataSetIterator
-
- totalOutcomes() - Method in class org.deeplearning4j.models.word2vec.iterator.Word2VecDataFetcher
-
- totalOutcomes() - Method in class org.deeplearning4j.models.word2vec.iterator.Word2VecDataSetIterator
-
- totalOutcomes - Variable in class org.deeplearning4j.spark.iterator.BaseDataSetIterator
-
- totalOutcomes() - Method in class org.deeplearning4j.spark.iterator.BaseDataSetIterator
-
- totalOutcomes() - Method in class org.deeplearning4j.spark.parameterserver.iterators.VirtualDataSetIterator
-
- totalRuntimeMs() - Method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder.PerformanceDecoder
-
- totalRuntimeMs(long) - Method in class org.deeplearning4j.ui.stats.sbe.UpdateEncoder.PerformanceEncoder
-
- totalRuntimeMsId() - Static method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder.PerformanceDecoder
-
- totalRuntimeMsMaxValue() - Static method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder.PerformanceDecoder
-
- totalRuntimeMsMaxValue() - Static method in class org.deeplearning4j.ui.stats.sbe.UpdateEncoder.PerformanceEncoder
-
- totalRuntimeMsMetaAttribute(MetaAttribute) - Static method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder.PerformanceDecoder
-
- totalRuntimeMsMinValue() - Static method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder.PerformanceDecoder
-
- totalRuntimeMsMinValue() - Static method in class org.deeplearning4j.ui.stats.sbe.UpdateEncoder.PerformanceEncoder
-
- totalRuntimeMsNullValue() - Static method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder.PerformanceDecoder
-
- totalRuntimeMsNullValue() - Static method in class org.deeplearning4j.ui.stats.sbe.UpdateEncoder.PerformanceEncoder
-
- totalWordOccurrences() - Method in class org.deeplearning4j.models.word2vec.wordstore.inmemory.AbstractCache
-
Returns total number of elements observed
- totalWordOccurrences() - Method in class org.deeplearning4j.models.word2vec.wordstore.inmemory.InMemoryLookupCache
-
Deprecated.
The total number of word occurrences
- totalWordOccurrences() - Method in interface org.deeplearning4j.models.word2vec.wordstore.VocabCache
-
The total number of word occurrences
- totalWords(int) - Method in class org.deeplearning4j.spark.models.embeddings.word2vec.Word2VecParam.Builder
-
Deprecated.
- totalWords() - Method in interface org.deeplearning4j.text.invertedindex.InvertedIndex
-
Total number of words in the index
- totalWordsBeyondLimit() - Method in class org.deeplearning4j.models.word2vec.wordstore.VocabularyHolder
-
- toText() - Method in class org.ansj.domain.AnsjItem
-
- toTree(TreebankNode, Pair<String, MultiDimensionalMap<Integer, Integer, String>>) - Static method in class org.deeplearning4j.text.corpora.treeparser.TreeFactory
-
Converts a treebank node to a tree
- toTree(TreebankNode) - Static method in class org.deeplearning4j.text.corpora.treeparser.TreeFactory
-
Converts a treebank node to a tree
- touch() - Method in class org.deeplearning4j.optimize.solvers.accumulation.BasicGradientsAccumulator
-
This method does initialization of given worker wrt Thread-Device Affinity
- touch() - Method in class org.deeplearning4j.optimize.solvers.accumulation.EncodedGradientsAccumulator
-
This method does initialization of given worker wrt Thread-Device Affinity
- touch() - Method in interface org.deeplearning4j.optimize.solvers.accumulation.GradientsAccumulator
-
This method does initialization of given worker wrt Thread-Device Affinity
- toValue() - Method in class org.ansj.domain.Term
-
- toVector(Vector) - Static method in class org.deeplearning4j.spark.util.MLLibUtil
-
Convert an ndarray to a vector
- toVector(INDArray) - Static method in class org.deeplearning4j.spark.util.MLLibUtil
-
Convert an ndarray to a vector
- toYaml() - Method in class org.deeplearning4j.eval.BaseEvaluation
-
- toYaml() - Method in class org.deeplearning4j.eval.curves.BaseCurve
-
- toYaml() - Method in class org.deeplearning4j.eval.curves.BaseHistogram
-
- toYaml() - Method in interface org.deeplearning4j.eval.IEvaluation
-
- toYaml() - Method in class org.deeplearning4j.nn.conf.ComputationGraphConfiguration
-
- toYaml() - Method in class org.deeplearning4j.nn.conf.memory.MemoryReport
-
- toYaml() - Method in class org.deeplearning4j.nn.conf.MultiLayerConfiguration
-
- toYaml() - Method in class org.deeplearning4j.nn.conf.NeuralNetConfiguration
-
Return this configuration as json
- toYaml() - Method in class org.deeplearning4j.nn.transferlearning.FineTuneConfiguration
-
- toYaml() - Method in class org.deeplearning4j.perf.listener.HardwareMetric
-
- toYaml() - Method in interface org.deeplearning4j.spark.api.TrainingMaster
-
Get the TrainingMaster configuration as YAML
- toYaml() - Method in class org.deeplearning4j.spark.impl.paramavg.ParameterAveragingTrainingMaster
-
- toYaml() - Method in class org.deeplearning4j.spark.parameterserver.training.SharedTrainingMaster
-
- trackEpochs() - Method in class org.deeplearning4j.datasets.iterator.MultipleEpochsIterator
-
Deprecated.
- train - Variable in class org.deeplearning4j.datasets.fetchers.MnistDataFetcher
-
- train - Variable in class org.deeplearning4j.datasets.iterator.impl.CifarDataSetIterator
-
- train(JavaRDD<String>) - Method in class org.deeplearning4j.spark.models.embeddings.glove.Glove
-
Train on the corpus
- train(JavaRDD<String>) - Method in class org.deeplearning4j.spark.models.embeddings.word2vec.Word2Vec
-
Training word2vec model on a given text corpus
- trainAllAtOnce(List<Sequence<ShallowSequenceElement>>) - Method in class org.deeplearning4j.spark.models.sequencevectors.functions.PartitionTrainingFunction
-
- trainElementsRepresentation(boolean) - Method in class org.deeplearning4j.models.glove.Glove.Builder
-
- trainElementsRepresentation(boolean) - Method in class org.deeplearning4j.models.node2vec.Node2Vec.Builder
-
Deprecated.
- trainElementsRepresentation(boolean) - Method in class org.deeplearning4j.models.paragraphvectors.ParagraphVectors.Builder
-
This method defines, if words representation should be build together with documents representations.
- trainElementsRepresentation(boolean) - Method in class org.deeplearning4j.models.sequencevectors.SequenceVectors.Builder
-
- trainElementsRepresentation(boolean) - Method in class org.deeplearning4j.models.word2vec.Word2Vec.Builder
-
This method is hardcoded to TRUE, since that's whole point of Word2Vec
- trainElementsVectors - Variable in class org.deeplearning4j.models.embeddings.wordvectors.WordVectorsImpl
-
- trainElementsVectors - Variable in class org.deeplearning4j.models.sequencevectors.SequenceVectors.Builder
-
- Trainer - Interface in org.deeplearning4j.parallelism.trainer
-
A Trainer is an individual worker used in
ParallelWrapper
for handling training in multi core situations.
- TrainerContext - Interface in org.deeplearning4j.parallelism.factory
-
- trainerContext - Variable in class org.deeplearning4j.parallelism.ParallelWrapper.Builder
-
- trainerContext - Variable in class org.deeplearning4j.parallelism.ParallelWrapper
-
- trainerContextArgs - Variable in class org.deeplearning4j.parallelism.ParallelWrapper.Builder
-
- trainerContextArgs(Object...) - Method in class org.deeplearning4j.parallelism.ParallelWrapper.Builder
-
- trainerContextArgs - Variable in class org.deeplearning4j.parallelism.ParallelWrapper
-
- trainerFactory(TrainerContext) - Method in class org.deeplearning4j.parallelism.ParallelWrapper.Builder
-
- TRAINING_FILE_LABELS_FILENAME_UNZIPPED - Static variable in class org.deeplearning4j.base.MnistFetcher
-
- TRAINING_FILES_FILENAME_UNZIPPED - Static variable in class org.deeplearning4j.base.MnistFetcher
-
- trainingArchive - Variable in class org.deeplearning4j.nn.modelimport.keras.utils.KerasModelBuilder
-
- trainingDriver - Variable in class org.deeplearning4j.spark.parameterserver.training.SharedTrainingMaster
-
- TrainingFunction<T extends SequenceElement> - Class in org.deeplearning4j.spark.models.sequencevectors.functions
-
This is wrapper for SequenceVectors training over given Sequence
- TrainingFunction(Broadcast<VocabCache<ShallowSequenceElement>>, Broadcast<VectorsConfiguration>, Broadcast<VoidConfiguration>) - Constructor for class org.deeplearning4j.spark.models.sequencevectors.functions.TrainingFunction
-
- TrainingHook - Interface in org.deeplearning4j.spark.api
-
A hook for the workers when training.
- trainingHookList - Variable in class org.deeplearning4j.spark.impl.paramavg.ParameterAveragingTrainingMaster
-
- trainingHooks - Variable in class org.deeplearning4j.spark.impl.paramavg.ParameterAveragingTrainingMaster.Builder
-
- trainingHooks(Collection<TrainingHook>) - Method in class org.deeplearning4j.spark.impl.paramavg.ParameterAveragingTrainingMaster.Builder
-
Adds training hooks to the master.
- trainingHooks(TrainingHook...) - Method in class org.deeplearning4j.spark.impl.paramavg.ParameterAveragingTrainingMaster.Builder
-
Adds training hooks to the master.
- trainingHooks - Variable in class org.deeplearning4j.spark.parameterserver.training.SharedTrainingMaster
-
- trainingJson - Variable in class org.deeplearning4j.nn.modelimport.keras.utils.KerasModelBuilder
-
- trainingJson(String) - Method in class org.deeplearning4j.nn.modelimport.keras.utils.KerasModelBuilder
-
- trainingJsonInputStream(InputStream) - Method in class org.deeplearning4j.nn.modelimport.keras.utils.KerasModelBuilder
-
- TrainingListener - Interface in org.deeplearning4j.optimize.api
-
A listener interface for training DL4J models.
The methods here will be called at various points during training, and only during training.
Note that users can extend
BaseTrainingListener and selectively override the required methods,
instead of implementing TrainingListener directly and having a number of no-op methods.
- TrainingListener - Variable in class org.deeplearning4j.plot.BarnesHutTsne
-
- trainingListeners - Variable in class org.deeplearning4j.nn.layers.AbstractLayer
-
- trainingListeners - Variable in class org.deeplearning4j.nn.layers.variational.VariationalAutoencoder
-
- trainingListeners - Variable in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
-
- trainingListeners - Variable in class org.deeplearning4j.optimize.solvers.BaseOptimizer
-
- TrainingMaster<R extends TrainingResult,W extends TrainingWorker<R>> - Interface in org.deeplearning4j.spark.api
-
A TrainingMaster controls how distributed training is executed in practice
In principle, a large number of different approches can be used in distributed training (synchronous vs.
- trainingMaster - Variable in class org.deeplearning4j.spark.impl.SparkListenable
-
- trainingMasterSpecificStats(SparkTrainingStats) - Method in class org.deeplearning4j.spark.api.stats.CommonSparkTrainingStats.Builder
-
- trainingMasterUID - Variable in class org.deeplearning4j.spark.impl.paramavg.BaseTrainingMaster
-
- trainingMode - Variable in class org.deeplearning4j.parallelism.ParallelWrapper.Builder
-
- trainingMode(ParallelWrapper.TrainingMode) - Method in class org.deeplearning4j.parallelism.ParallelWrapper.Builder
-
This method allows you to specify training mode for this instance of PW.
- TrainingResult - Interface in org.deeplearning4j.spark.api
-
TrainingResult: a class used by
TrainingMaster implementations
Each TrainingMaster will have its own type of training result.
- TrainingWorker<R extends TrainingResult> - Interface in org.deeplearning4j.spark.api
-
TrainingWorker is a small serializable class that can be passed (in serialized form) to each Spark executor
for actually conducting training.
- trainingWorkspaceMode - Variable in class org.deeplearning4j.nn.conf.ComputationGraphConfiguration
-
- trainingWorkspaceMode - Variable in class org.deeplearning4j.nn.conf.MultiLayerConfiguration.Builder
-
- trainingWorkspaceMode(WorkspaceMode) - Method in class org.deeplearning4j.nn.conf.MultiLayerConfiguration.Builder
-
- trainingWorkspaceMode - Variable in class org.deeplearning4j.nn.conf.MultiLayerConfiguration
-
- trainingWorkspaceMode - Variable in class org.deeplearning4j.nn.conf.NeuralNetConfiguration.Builder
-
- trainingWorkspaceMode(WorkspaceMode) - Method in class org.deeplearning4j.nn.conf.NeuralNetConfiguration.Builder
-
This method defines Workspace mode being used during training:
NONE: workspace won't be used
ENABLED: workspaces will be used for training (reduced memory and better performance)
- trainingWorkspaceMode(WorkspaceMode) - Method in class org.deeplearning4j.nn.transferlearning.FineTuneConfiguration.Builder
-
This method defines Workspace mode being used during training:
NONE: workspace won't be used
ENABLED: workspaces will be used for training (reduced memory and better performance)
- trainingWorkspaceMode - Variable in class org.deeplearning4j.nn.transferlearning.FineTuneConfiguration
-
- TrainModule - Class in org.deeplearning4j.ui.module.train
-
Main DL4J Training UI
- TrainModule() - Constructor for class org.deeplearning4j.ui.module.train.TrainModule
-
- TrainModuleUtils - Class in org.deeplearning4j.ui.module.train
-
- TrainModuleUtils() - Constructor for class org.deeplearning4j.ui.module.train.TrainModuleUtils
-
- TrainModuleUtils.GraphInfo - Class in org.deeplearning4j.ui.module.train
-
- trainSentence(List<VocabWord>, double) - Method in class org.deeplearning4j.spark.models.embeddings.word2vec.FirstIterationFunctionAdapter
-
- trainSentence(Word2VecParam, List<VocabWord>, double, List<Triple<Integer, Integer, Integer>>) - Method in class org.deeplearning4j.spark.models.embeddings.word2vec.SentenceBatch
-
Deprecated.
Train on a list of vocab words
- trainSentence(List<VocabWord>, double) - Method in class org.deeplearning4j.spark.models.embeddings.word2vec.Word2VecPerformer
-
Deprecated.
Train on a list of vocab words
- trainSentence(List<VocabWord>, double) - Method in class org.deeplearning4j.spark.models.embeddings.word2vec.Word2VecPerformerVoid
-
Deprecated.
Train on a list of vocab words
- trainSequence(Sequence<T>, AtomicLong, double) - Method in class org.deeplearning4j.models.sequencevectors.SequenceVectors
-
- trainSequencesRepresentation(boolean) - Method in class org.deeplearning4j.models.glove.Glove.Builder
-
Deprecated.
- trainSequencesRepresentation(boolean) - Method in class org.deeplearning4j.models.node2vec.Node2Vec.Builder
-
Deprecated.
- trainSequencesRepresentation(boolean) - Method in class org.deeplearning4j.models.paragraphvectors.ParagraphVectors.Builder
-
This method is hardcoded to TRUE, since that's whole point of ParagraphVectors
- trainSequencesRepresentation(boolean) - Method in class org.deeplearning4j.models.sequencevectors.SequenceVectors.Builder
-
- trainSequencesRepresentation(boolean) - Method in class org.deeplearning4j.models.word2vec.Word2Vec.Builder
-
This method is hardcoded to FALSE, since that's whole point of Word2Vec
- trainSequenceVectors - Variable in class org.deeplearning4j.models.embeddings.wordvectors.WordVectorsImpl
-
- trainSequenceVectors - Variable in class org.deeplearning4j.models.sequencevectors.SequenceVectors.Builder
-
- trainWordVectors(boolean) - Method in class org.deeplearning4j.models.paragraphvectors.ParagraphVectors.Builder
-
This method defines, if words representations should be build together with documents representations.
- transferBackToVocabCache() - Method in class org.deeplearning4j.models.word2vec.wordstore.VocabularyHolder
-
- transferBackToVocabCache(VocabCache) - Method in class org.deeplearning4j.models.word2vec.wordstore.VocabularyHolder
-
- transferBackToVocabCache(VocabCache, boolean) - Method in class org.deeplearning4j.models.word2vec.wordstore.VocabularyHolder
-
This method is required for compatibility purposes.
- TransferLearning - Class in org.deeplearning4j.nn.transferlearning
-
The transfer learning API can be used to modify the architecture or the learning parameters of an existing multilayernetwork or computation graph.
- TransferLearning() - Constructor for class org.deeplearning4j.nn.transferlearning.TransferLearning
-
- TransferLearning.Builder - Class in org.deeplearning4j.nn.transferlearning
-
- TransferLearning.GraphBuilder - Class in org.deeplearning4j.nn.transferlearning
-
- TransferLearningHelper - Class in org.deeplearning4j.nn.transferlearning
-
This class is intended for use with the transfer learning API.
- TransferLearningHelper(ComputationGraph, String...) - Constructor for class org.deeplearning4j.nn.transferlearning.TransferLearningHelper
-
Will modify the given comp graph (in place!) to freeze vertices from input to the vertex specified.
- TransferLearningHelper(ComputationGraph) - Constructor for class org.deeplearning4j.nn.transferlearning.TransferLearningHelper
-
Expects a computation graph where some vertices are frozen
- TransferLearningHelper(MultiLayerNetwork, int) - Constructor for class org.deeplearning4j.nn.transferlearning.TransferLearningHelper
-
Will modify the given MLN (in place!) to freeze layers (hold params constant during training) specified and below
- TransferLearningHelper(MultiLayerNetwork) - Constructor for class org.deeplearning4j.nn.transferlearning.TransferLearningHelper
-
Expects a MLN where some layers are frozen
- transform(String) - Method in class org.deeplearning4j.bagofwords.vectorizer.BagOfWordsVectorizer
-
- transform(List<String>) - Method in class org.deeplearning4j.bagofwords.vectorizer.BagOfWordsVectorizer
-
- transform(String) - Method in interface org.deeplearning4j.bagofwords.vectorizer.TextVectorizer
-
Transforms the matrix
- transform(List<String>) - Method in interface org.deeplearning4j.bagofwords.vectorizer.TextVectorizer
-
Transforms the matrix
- transform(String) - Method in class org.deeplearning4j.bagofwords.vectorizer.TfidfVectorizer
-
Transforms the matrix
- transform(List<String>) - Method in class org.deeplearning4j.bagofwords.vectorizer.TfidfVectorizer
-
- transform(Tree) - Method in class org.deeplearning4j.text.corpora.treeparser.BinarizeTreeTransformer
-
- transform(Tree) - Method in class org.deeplearning4j.text.corpora.treeparser.CollapseUnaries
-
- transform(Tree) - Method in interface org.deeplearning4j.text.corpora.treeparser.transformer.TreeTransformer
-
Applies a applyTransformToOrigin to a tree
- transform() - Method in class org.deeplearning4j.text.inputsanitation.InputHomogenization
-
Returns the normalized text passed in via constructor
- transformProcess() - Method in interface org.deeplearning4j.spark.data.DataSetProvider
-
(Optional) The transform process
for the dataset provider.
- transformProcess() - Method in interface org.deeplearning4j.spark.data.MultiDataSetProvider
-
(Optional) The transform process
for the dataset provider.
- transformToSequence(String) - Method in class org.deeplearning4j.models.sequencevectors.transformers.impl.SentenceTransformer
-
- transformToSequence(V) - Method in interface org.deeplearning4j.models.sequencevectors.transformers.SequenceTransformer
-
This is generic method for transformation data from any format to Sequence of SequenceElement.
- transport - Variable in class org.deeplearning4j.spark.parameterserver.networking.SilentTrainingDriver
-
- transport - Variable in class org.deeplearning4j.spark.parameterserver.training.SharedTrainingMaster.Builder
-
- transport(Transport) - Method in class org.deeplearning4j.spark.parameterserver.training.SharedTrainingMaster.Builder
-
Optional method: Transport implementation to be used as TransportType.CUSTOM for VoidParameterAveraging method
- transport - Variable in class org.deeplearning4j.spark.parameterserver.training.SharedTrainingMaster
-
- transpose() - Method in interface org.deeplearning4j.nn.api.Layer
-
Deprecated.
- transpose() - Method in class org.deeplearning4j.nn.layers.AbstractLayer
-
- transpose() - Method in class org.deeplearning4j.nn.layers.ActivationLayer
-
- transpose() - Method in class org.deeplearning4j.nn.layers.BaseLayer
-
- transpose() - Method in class org.deeplearning4j.nn.layers.convolution.ConvolutionLayer
-
- transpose() - Method in class org.deeplearning4j.nn.layers.convolution.SpaceToBatch
-
- transpose() - Method in class org.deeplearning4j.nn.layers.convolution.SpaceToDepth
-
- transpose() - Method in class org.deeplearning4j.nn.layers.convolution.subsampling.Subsampling3DLayer
-
- transpose() - Method in class org.deeplearning4j.nn.layers.convolution.subsampling.SubsamplingLayer
-
- transpose() - Method in class org.deeplearning4j.nn.layers.convolution.upsampling.Upsampling2D
-
- transpose() - Method in class org.deeplearning4j.nn.layers.convolution.upsampling.Upsampling3D
-
- transpose() - Method in class org.deeplearning4j.nn.layers.DropoutLayer
-
- transpose() - Method in class org.deeplearning4j.nn.layers.LossLayer
-
- transpose() - Method in class org.deeplearning4j.nn.layers.normalization.BatchNormalization
-
- transpose() - Method in class org.deeplearning4j.nn.layers.normalization.LocalResponseNormalization
-
- transpose() - Method in class org.deeplearning4j.nn.layers.recurrent.BidirectionalLayer
-
- transpose() - Method in class org.deeplearning4j.nn.layers.recurrent.GravesBidirectionalLSTM
-
- transpose() - Method in class org.deeplearning4j.nn.layers.recurrent.GravesLSTM
-
- transpose() - Method in class org.deeplearning4j.nn.layers.recurrent.LSTM
-
- transpose() - Method in class org.deeplearning4j.nn.layers.variational.VariationalAutoencoder
-
- transpose() - Method in class org.deeplearning4j.nn.layers.wrapper.BaseWrapperLayer
-
- transpose() - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
-
- tree - Variable in class org.deeplearning4j.graph.models.embeddings.InMemoryGraphLookupTable
-
- Tree - Class in org.deeplearning4j.nn.layers.feedforward.autoencoder.recursive
-
Tree for a recursive neural tensor network
based on Socher et al's work.
- Tree(Tree) - Constructor for class org.deeplearning4j.nn.layers.feedforward.autoencoder.recursive.Tree
-
Clone constructor (all but the children)
- Tree(Tree, List<String>) - Constructor for class org.deeplearning4j.nn.layers.feedforward.autoencoder.recursive.Tree
-
- Tree(List<String>) - Constructor for class org.deeplearning4j.nn.layers.feedforward.autoencoder.recursive.Tree
-
- TreeFactory - Class in org.deeplearning4j.text.corpora.treeparser
-
Static movingwindow class handling the conversion of
treebank nodes to Trees useful
for recursive neural tensor networks
- TreeIterator - Class in org.deeplearning4j.text.corpora.treeparser
-
Tree iterator: iterate over sentences
returning trees with labels and everything already
preset
- TreeIterator(LabelAwareSentenceIterator, List<String>, TreeVectorizer, int) - Constructor for class org.deeplearning4j.text.corpora.treeparser.TreeIterator
-
- TreeIterator(LabelAwareSentenceIterator, List<String>, TreeVectorizer) - Constructor for class org.deeplearning4j.text.corpora.treeparser.TreeIterator
-
- TreeIterator(LabelAwareSentenceIterator, List<String>) - Constructor for class org.deeplearning4j.text.corpora.treeparser.TreeIterator
-
- TreeModelUtils<T extends SequenceElement> - Class in org.deeplearning4j.models.embeddings.reader.impl
-
This is VPTree-based implementation for wordsNearest method, suited for multiple consequent calls.
- TreeModelUtils() - Constructor for class org.deeplearning4j.models.embeddings.reader.impl.TreeModelUtils
-
- TreeParser - Class in org.deeplearning4j.text.corpora.treeparser
-
Tree parser for constituency parsing
- TreeParser(AnalysisEngine, AnalysisEngine, CasPool) - Constructor for class org.deeplearning4j.text.corpora.treeparser.TreeParser
-
- TreeParser() - Constructor for class org.deeplearning4j.text.corpora.treeparser.TreeParser
-
- TreeTransformer - Interface in org.deeplearning4j.text.corpora.treeparser.transformer
-
Tree transformer
- TreeVectorizer - Class in org.deeplearning4j.text.corpora.treeparser
-
Tree vectorization pipeline.
- TreeVectorizer(TreeParser) - Constructor for class org.deeplearning4j.text.corpora.treeparser.TreeVectorizer
-
Uses the given parser and model
for vectorization of strings
- TreeVectorizer() - Constructor for class org.deeplearning4j.text.corpora.treeparser.TreeVectorizer
-
Uses word vectors from the passed in word2vec model
- Trie - Class in com.atilika.kuromoji.trie
-
Simple Trie used to build the DoubleArrayTrie
- Trie() - Constructor for class com.atilika.kuromoji.trie.Trie
-
Constructor
- Trie.Node - Class in com.atilika.kuromoji.trie
-
Trie Node
- triggerEpochListeners(boolean, Model, int) - Method in class org.deeplearning4j.earlystopping.trainer.BaseEarlyStoppingTrainer
-
- trueNegatives - Variable in class org.deeplearning4j.eval.Evaluation
-
- trueNegatives() - Method in class org.deeplearning4j.eval.Evaluation
-
True negatives: correctly rejected
- trueNegatives(int) - Method in class org.deeplearning4j.eval.EvaluationBinary
-
Get the true negatives count for the specified output
- truePositives - Variable in class org.deeplearning4j.eval.Evaluation
-
- truePositives() - Method in class org.deeplearning4j.eval.Evaluation
-
True positives: correctly rejected
- truePositives(int) - Method in class org.deeplearning4j.eval.EvaluationBinary
-
Get the true positives count for the specified output
- truncatedBPTT - Variable in class org.deeplearning4j.nn.modelimport.keras.KerasModel
-
- TruncatedNormalDistribution - Class in org.deeplearning4j.nn.conf.distribution
-
A truncated normal distribution.
- TruncatedNormalDistribution(double, double) - Constructor for class org.deeplearning4j.nn.conf.distribution.TruncatedNormalDistribution
-
Create a truncated normal distribution
with the given mean and std
- truncateVocabulary() - Method in class org.deeplearning4j.models.word2vec.wordstore.VocabularyHolder
-
The same as truncateVocabulary(this.minWordFrequency)
- truncateVocabulary(int) - Method in class org.deeplearning4j.models.word2vec.wordstore.VocabularyHolder
-
All words with frequency below threshold wii be removed
- tryCompare(DataSet, DataSet) - Method in class org.deeplearning4j.spark.ordering.DataSetOrdering
-
- tryOpenBrowser(String, Logger) - Static method in class org.deeplearning4j.ui.UiUtils
-
- Tsne - Class in org.deeplearning4j.plot
-
dl4j port of original t-sne algorithm described/implemented by van der Maaten and Hinton
- Tsne(int, double, double, double, double, double, int, boolean, boolean, int, double, double, boolean, double) - Constructor for class org.deeplearning4j.plot.Tsne
-
- Tsne.Builder - Class in org.deeplearning4j.plot
-
- TsneModule - Class in org.deeplearning4j.ui.module.tsne
-
Created by Alex on 25/10/2016.
- TsneModule() - Constructor for class org.deeplearning4j.ui.module.tsne.TsneModule
-
- type - Variable in class org.deeplearning4j.clustering.strategy.BaseClusteringStrategy
-
- type - Variable in class org.deeplearning4j.earlystopping.scorecalc.ROCScoreCalculator
-
- type() - Method in interface org.deeplearning4j.nn.api.Layer
-
Returns the layer type
- type() - Method in class org.deeplearning4j.nn.layers.AbstractLayer
-
- type() - Method in class org.deeplearning4j.nn.layers.ActivationLayer
-
- type() - Method in class org.deeplearning4j.nn.layers.convolution.CnnLossLayer
-
- type() - Method in class org.deeplearning4j.nn.layers.convolution.ConvolutionLayer
-
- type() - Method in class org.deeplearning4j.nn.layers.convolution.Cropping1DLayer
-
- type() - Method in class org.deeplearning4j.nn.layers.convolution.Cropping2DLayer
-
- type() - Method in class org.deeplearning4j.nn.layers.convolution.Cropping3DLayer
-
- type() - Method in class org.deeplearning4j.nn.layers.convolution.SpaceToBatch
-
- type() - Method in class org.deeplearning4j.nn.layers.convolution.SpaceToDepth
-
- type() - Method in class org.deeplearning4j.nn.layers.convolution.subsampling.Subsampling3DLayer
-
- type() - Method in class org.deeplearning4j.nn.layers.convolution.subsampling.SubsamplingLayer
-
- type() - Method in class org.deeplearning4j.nn.layers.convolution.upsampling.Upsampling2D
-
- type() - Method in class org.deeplearning4j.nn.layers.convolution.upsampling.Upsampling3D
-
- type() - Method in class org.deeplearning4j.nn.layers.convolution.ZeroPadding1DLayer
-
- type() - Method in class org.deeplearning4j.nn.layers.convolution.ZeroPadding3DLayer
-
- type() - Method in class org.deeplearning4j.nn.layers.convolution.ZeroPaddingLayer
-
- type() - Method in class org.deeplearning4j.nn.layers.DropoutLayer
-
- type() - Method in class org.deeplearning4j.nn.layers.feedforward.embedding.EmbeddingSequenceLayer
-
- type() - Method in class org.deeplearning4j.nn.layers.LossLayer
-
- type() - Method in class org.deeplearning4j.nn.layers.normalization.BatchNormalization
-
- type() - Method in class org.deeplearning4j.nn.layers.normalization.LocalResponseNormalization
-
- type() - Method in class org.deeplearning4j.nn.layers.ocnn.OCNNOutputLayer
-
- type() - Method in class org.deeplearning4j.nn.layers.pooling.GlobalPoolingLayer
-
- type() - Method in class org.deeplearning4j.nn.layers.recurrent.BidirectionalLayer
-
- type() - Method in class org.deeplearning4j.nn.layers.recurrent.GravesBidirectionalLSTM
-
- type() - Method in class org.deeplearning4j.nn.layers.recurrent.GravesLSTM
-
- type() - Method in class org.deeplearning4j.nn.layers.recurrent.LastTimeStepLayer
-
- type() - Method in class org.deeplearning4j.nn.layers.recurrent.LSTM
-
- type() - Method in class org.deeplearning4j.nn.layers.recurrent.MaskZeroLayer
-
- type() - Method in class org.deeplearning4j.nn.layers.recurrent.RnnLossLayer
-
- type() - Method in class org.deeplearning4j.nn.layers.recurrent.RnnOutputLayer
-
- type() - Method in class org.deeplearning4j.nn.layers.variational.VariationalAutoencoder
-
- type() - Method in class org.deeplearning4j.nn.layers.wrapper.BaseWrapperLayer
-
- type() - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
-
- type - Variable in class org.deeplearning4j.parallelism.MagicQueue
-
Deprecated.
- TYPE_ID - Static variable in class org.deeplearning4j.ui.stats.BaseStatsListener
-
- typeID() - Method in class org.deeplearning4j.ui.stats.sbe.StaticInfoDecoder
-
- typeID(String) - Method in class org.deeplearning4j.ui.stats.sbe.StaticInfoEncoder
-
- typeID() - Method in class org.deeplearning4j.ui.stats.sbe.StorageMetaDataDecoder
-
- typeID(String) - Method in class org.deeplearning4j.ui.stats.sbe.StorageMetaDataEncoder
-
- typeID() - Method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder
-
- typeID(String) - Method in class org.deeplearning4j.ui.stats.sbe.UpdateEncoder
-
- typeIDCharacterEncoding() - Static method in class org.deeplearning4j.ui.stats.sbe.StaticInfoDecoder
-
- typeIDCharacterEncoding() - Static method in class org.deeplearning4j.ui.stats.sbe.StaticInfoEncoder
-
- typeIDCharacterEncoding() - Static method in class org.deeplearning4j.ui.stats.sbe.StorageMetaDataDecoder
-
- typeIDCharacterEncoding() - Static method in class org.deeplearning4j.ui.stats.sbe.StorageMetaDataEncoder
-
- typeIDCharacterEncoding() - Static method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder
-
- typeIDCharacterEncoding() - Static method in class org.deeplearning4j.ui.stats.sbe.UpdateEncoder
-
- typeIDHeaderLength() - Static method in class org.deeplearning4j.ui.stats.sbe.StaticInfoDecoder
-
- typeIDHeaderLength() - Static method in class org.deeplearning4j.ui.stats.sbe.StaticInfoEncoder
-
- typeIDHeaderLength() - Static method in class org.deeplearning4j.ui.stats.sbe.StorageMetaDataDecoder
-
- typeIDHeaderLength() - Static method in class org.deeplearning4j.ui.stats.sbe.StorageMetaDataEncoder
-
- typeIDHeaderLength() - Static method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder
-
- typeIDHeaderLength() - Static method in class org.deeplearning4j.ui.stats.sbe.UpdateEncoder
-
- typeIDId() - Static method in class org.deeplearning4j.ui.stats.sbe.StaticInfoDecoder
-
- typeIDId() - Static method in class org.deeplearning4j.ui.stats.sbe.StaticInfoEncoder
-
- typeIDId() - Static method in class org.deeplearning4j.ui.stats.sbe.StorageMetaDataDecoder
-
- typeIDId() - Static method in class org.deeplearning4j.ui.stats.sbe.StorageMetaDataEncoder
-
- typeIDId() - Static method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder
-
- typeIDId() - Static method in class org.deeplearning4j.ui.stats.sbe.UpdateEncoder
-
- typeIDLength() - Method in class org.deeplearning4j.ui.stats.sbe.StaticInfoDecoder
-
- typeIDLength() - Method in class org.deeplearning4j.ui.stats.sbe.StorageMetaDataDecoder
-
- typeIDLength() - Method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder
-
- typeIDMetaAttribute(MetaAttribute) - Static method in class org.deeplearning4j.ui.stats.sbe.StaticInfoDecoder
-
- typeIDMetaAttribute(MetaAttribute) - Static method in class org.deeplearning4j.ui.stats.sbe.StaticInfoEncoder
-
- typeIDMetaAttribute(MetaAttribute) - Static method in class org.deeplearning4j.ui.stats.sbe.StorageMetaDataDecoder
-
- typeIDMetaAttribute(MetaAttribute) - Static method in class org.deeplearning4j.ui.stats.sbe.StorageMetaDataEncoder
-
- typeIDMetaAttribute(MetaAttribute) - Static method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder
-
- typeIDMetaAttribute(MetaAttribute) - Static method in class org.deeplearning4j.ui.stats.sbe.UpdateEncoder
-
- typeSystemInit(TypeSystem) - Method in class org.deeplearning4j.text.annotator.PoStagger
-
Initializes the type system.
- typeSystemInit(TypeSystem) - Method in class org.deeplearning4j.text.tokenization.tokenizer.ConcurrentTokenizer
-
Initializes the type system.
- V_KEY - Static variable in class org.deeplearning4j.nn.layers.ocnn.OCNNParamInitializer
-
- VAEReconErrorScoreCalculator - Class in org.deeplearning4j.earlystopping.scorecalc
-
Score function for variational autoencoder reconstruction error for a MultiLayerNetwork or ComputationGraph.
VariationalAutoencoder layer must be first layer in the network
- VAEReconErrorScoreCalculator(RegressionEvaluation.Metric, DataSetIterator) - Constructor for class org.deeplearning4j.earlystopping.scorecalc.VAEReconErrorScoreCalculator
-
Constructor for reconstruction *ERROR*
- VAEReconProbScoreCalculator - Class in org.deeplearning4j.earlystopping.scorecalc
-
Score calculator for variational autoencoder reconstruction probability or reconstruction log probability for a
MultiLayerNetwork or ComputationGraph.
- VAEReconProbScoreCalculator(DataSetIterator, int, boolean) - Constructor for class org.deeplearning4j.earlystopping.scorecalc.VAEReconProbScoreCalculator
-
Constructor for average reconstruction probability
- VAEReconProbScoreCalculator(DataSetIterator, int, boolean, boolean) - Constructor for class org.deeplearning4j.earlystopping.scorecalc.VAEReconProbScoreCalculator
-
Constructor for reconstruction probability
- VaeReconstructionErrorWithKeyFunction<K> - Class in org.deeplearning4j.spark.impl.multilayer.scoring
-
Function to calculate the reconstruction error for a variational autoencoder, that is the first layer in a
MultiLayerNetwork.
Note that the VAE must be using a loss function, not a
ReconstructionDistribution
Also note that scoring is batched for computational efficiency.
- VaeReconstructionErrorWithKeyFunction(Broadcast<INDArray>, Broadcast<String>, int) - Constructor for class org.deeplearning4j.spark.impl.multilayer.scoring.VaeReconstructionErrorWithKeyFunction
-
- VaeReconstructionProbWithKeyFunction<K> - Class in org.deeplearning4j.spark.impl.multilayer.scoring
-
Function to calculate the reconstruction probability for a variational autoencoder, that is the first layer in a
MultiLayerNetwork.
Note that scoring is batched for computational efficiency.
- VaeReconstructionProbWithKeyFunction(Broadcast<INDArray>, Broadcast<String>, boolean, int, int) - Constructor for class org.deeplearning4j.spark.impl.multilayer.scoring.VaeReconstructionProbWithKeyFunction
-
- validate() - Method in class org.deeplearning4j.earlystopping.EarlyStoppingConfiguration
-
- validate() - Method in class org.deeplearning4j.nn.conf.ComputationGraphConfiguration
-
Check the configuration, make sure it is valid
- validate(boolean, boolean) - Method in class org.deeplearning4j.nn.conf.ComputationGraphConfiguration
-
Check the configuration, make sure it is valid
- validate() - Method in class org.deeplearning4j.nn.modelexport.solr.ltr.model.ScoringModel
-
- validateArrayLocation(ArrayType, INDArray, boolean, boolean) - Method in class org.deeplearning4j.nn.workspace.LayerWorkspaceMgr
-
- validateArrayShape(int[], INDArray) - Static method in class org.deeplearning4j.spark.util.data.validation.ValidateDataSetFn
-
- validateArrayWorkspaces(LayerWorkspaceMgr, INDArray, ArrayType, String, boolean, String) - Method in class org.deeplearning4j.nn.graph.ComputationGraph
-
- validateArrayWorkspaces(LayerWorkspaceMgr, INDArray, ArrayType, int, boolean, String) - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
-
- validateCnn3DKernelStridePadding(int[], int[], int[]) - Static method in class org.deeplearning4j.util.Convolution3DUtils
-
Perform validation on the CNN3D layer kernel/stride/padding.
- validateCnnKernelStridePadding(int[], int[], int[]) - Static method in class org.deeplearning4j.util.ConvolutionUtils
-
Perform validation on the CNN layer kernel/stride/padding.
- validateConfiguration() - Method in class org.deeplearning4j.spark.models.paragraphvectors.SparkParagraphVectors
-
- validateConfiguration() - Method in class org.deeplearning4j.spark.models.sequencevectors.SparkSequenceVectors
-
- validateConfiguration() - Method in class org.deeplearning4j.spark.models.word2vec.SparkWord2Vec
-
- validateConvolutionModePadding(ConvolutionMode, int[]) - Static method in class org.deeplearning4j.util.ConvolutionUtils
-
Check that the convolution mode is consistent with the padding specification
- ValidateDataSetFn - Class in org.deeplearning4j.spark.util.data.validation
-
- ValidateDataSetFn(boolean, int[], int[]) - Constructor for class org.deeplearning4j.spark.util.data.validation.ValidateDataSetFn
-
- validateDataSets(JavaSparkContext, String) - Static method in class org.deeplearning4j.spark.util.data.SparkDataValidation
-
Validate DataSet objects saved to the specified directory on HDFS by attempting to load them and checking their
contents.
- validateDataSets(JavaSparkContext, String, int[], int[]) - Static method in class org.deeplearning4j.spark.util.data.SparkDataValidation
-
Validate DataSet objects saved to the specified directory on HDFS by attempting to load them and checking their
contents.
- validateDataSets(SparkContext, String, boolean, boolean, int[], int[]) - Static method in class org.deeplearning4j.spark.util.data.SparkDataValidation
-
- validateDataSets(JavaSparkContext, String, boolean, boolean, int[], int[]) - Static method in class org.deeplearning4j.spark.util.data.SparkDataValidation
-
- validateEvent(ListenerEvent, long) - Method in interface org.deeplearning4j.models.sequencevectors.interfaces.VectorsListener
-
This method is called prior each processEvent call, to check if this specific VectorsListener implementation is viable for specific event
- validateEvent(ListenerEvent, long) - Method in class org.deeplearning4j.models.sequencevectors.listeners.ScoreListener
-
Deprecated.
- validateEvent(ListenerEvent, long) - Method in class org.deeplearning4j.models.sequencevectors.listeners.SerializingListener
-
This method is called prior each processEvent call, to check if this specific VectorsListener implementation is viable for specific event
- validateEvent(ListenerEvent, long) - Method in class org.deeplearning4j.models.sequencevectors.listeners.SimilarityListener
-
- validateInput() - Method in interface org.deeplearning4j.nn.api.Model
-
- validateInput() - Method in class org.deeplearning4j.nn.graph.ComputationGraph
-
- validateInput() - Method in class org.deeplearning4j.nn.layers.AbstractLayer
-
- validateInput() - Method in class org.deeplearning4j.nn.layers.recurrent.BidirectionalLayer
-
- validateInput() - Method in class org.deeplearning4j.nn.layers.variational.VariationalAutoencoder
-
- validateInput() - Method in class org.deeplearning4j.nn.layers.wrapper.BaseWrapperLayer
-
- validateInput() - Method in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
-
- validateInput() - Method in class org.deeplearning4j.plot.BarnesHutTsne
-
- validateModel() - Method in class org.deeplearning4j.nn.modelexport.solr.ltr.model.ScoringModel
-
- ValidateMultiDataSetFn - Class in org.deeplearning4j.spark.util.data.validation
-
- ValidateMultiDataSetFn(boolean, int, int, List<int[]>, List<int[]>) - Constructor for class org.deeplearning4j.spark.util.data.validation.ValidateMultiDataSetFn
-
- validateMultiDataSets(JavaSparkContext, String) - Static method in class org.deeplearning4j.spark.util.data.SparkDataValidation
-
Validate MultiDataSet objects saved to the specified directory on HDFS by attempting to load them and checking their
contents.
- validateMultiDataSets(JavaSparkContext, String, int, int) - Static method in class org.deeplearning4j.spark.util.data.SparkDataValidation
-
Validate MultiDataSet objects saved to the specified directory on HDFS by attempting to load them and checking their
contents.
- validateMultiDataSets(JavaSparkContext, String, List<int[]>, List<int[]>) - Static method in class org.deeplearning4j.spark.util.data.SparkDataValidation
-
Validate MultiDataSet objects saved to the specified directory on HDFS by attempting to load them and checking their
contents.
- validateMultiDataSets(SparkContext, String, boolean, boolean, int, int, List<int[]>, List<int[]>) - Static method in class org.deeplearning4j.spark.util.data.SparkDataValidation
-
- validateMultiDataSets(JavaSparkContext, String, boolean, boolean, int, int, List<int[]>, List<int[]>) - Static method in class org.deeplearning4j.spark.util.data.SparkDataValidation
-
- validateShapes(INDArray, int[], int[], int[], ConvolutionMode, int[], int[], boolean) - Static method in class org.deeplearning4j.util.ConvolutionUtils
-
- ValidationResult - Class in org.deeplearning4j.spark.util.data
-
Result for validation of DataSet and MultiDataSets.
- ValidationResult() - Constructor for class org.deeplearning4j.spark.util.data.ValidationResult
-
- ValidationResultReduceFn - Class in org.deeplearning4j.spark.util.data.validation
-
- ValidationResultReduceFn() - Constructor for class org.deeplearning4j.spark.util.data.validation.ValidationResultReduceFn
-
- value() - Method in class org.deeplearning4j.nn.layers.feedforward.autoencoder.recursive.Tree
-
- value() - Method in enum org.deeplearning4j.ui.stats.sbe.MemoryType
-
- value() - Method in enum org.deeplearning4j.ui.stats.sbe.StatSource
-
- value() - Method in enum org.deeplearning4j.ui.stats.sbe.StatsType
-
- value() - Method in enum org.deeplearning4j.ui.stats.sbe.StatType
-
- value() - Method in enum org.deeplearning4j.ui.stats.sbe.SummaryType
-
- value() - Method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder.PerParameterStatsDecoder.SummaryStatDecoder
-
- value(double) - Method in class org.deeplearning4j.ui.stats.sbe.UpdateEncoder.PerParameterStatsEncoder.SummaryStatEncoder
-
- valueId() - Static method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder.PerParameterStatsDecoder.SummaryStatDecoder
-
- valueMaxValue() - Static method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder.PerParameterStatsDecoder.SummaryStatDecoder
-
- valueMaxValue() - Static method in class org.deeplearning4j.ui.stats.sbe.UpdateEncoder.PerParameterStatsEncoder.SummaryStatEncoder
-
- valueMetaAttribute(MetaAttribute) - Static method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder.PerParameterStatsDecoder.SummaryStatDecoder
-
- valueMinValue() - Static method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder.PerParameterStatsDecoder.SummaryStatDecoder
-
- valueMinValue() - Static method in class org.deeplearning4j.ui.stats.sbe.UpdateEncoder.PerParameterStatsEncoder.SummaryStatEncoder
-
- valueNullValue() - Static method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder.PerParameterStatsDecoder.SummaryStatDecoder
-
- valueNullValue() - Static method in class org.deeplearning4j.ui.stats.sbe.UpdateEncoder.PerParameterStatsEncoder.SummaryStatEncoder
-
- valueOf(String) - Static method in enum com.atilika.kuromoji.TokenizerBase.Mode
-
Returns the enum constant of this type with the specified name.
- valueOf(String) - Static method in enum com.atilika.kuromoji.viterbi.ViterbiNode.Type
-
Returns the enum constant of this type with the specified name.
- valueOf(String) - Static method in enum org.ansj.util.TermUtil.InsertTermType
-
Returns the enum constant of this type with the specified name.
- valueOf(String) - Static method in enum org.deeplearning4j.api.storage.StatsStorageListener.EventType
-
Returns the enum constant of this type with the specified name.
- valueOf(String) - Static method in enum org.deeplearning4j.api.storage.StorageType
-
Returns the enum constant of this type with the specified name.
- valueOf(String) - Static method in enum org.deeplearning4j.clustering.optimisation.ClusteringOptimizationType
-
Returns the enum constant of this type with the specified name.
- valueOf(String) - Static method in enum org.deeplearning4j.clustering.strategy.ClusteringStrategyType
-
Returns the enum constant of this type with the specified name.
- valueOf(String) - Static method in enum org.deeplearning4j.datasets.datavec.RecordReaderMultiDataSetIterator.AlignmentMode
-
Returns the enum constant of this type with the specified name.
- valueOf(String) - Static method in enum org.deeplearning4j.datasets.datavec.SequenceRecordReaderDataSetIterator.AlignmentMode
-
Returns the enum constant of this type with the specified name.
- valueOf(String) - Static method in enum org.deeplearning4j.datasets.fetchers.DataSetType
-
Returns the enum constant of this type with the specified name.
- valueOf(String) - Static method in enum org.deeplearning4j.datasets.iterator.impl.EmnistDataSetIterator.Set
-
Returns the enum constant of this type with the specified name.
- valueOf(String) - Static method in enum org.deeplearning4j.datasets.rearrange.LocalUnstructuredDataFormatter.LabelingType
-
Returns the enum constant of this type with the specified name.
- valueOf(String) - Static method in enum org.deeplearning4j.earlystopping.EarlyStoppingResult.TerminationReason
-
Returns the enum constant of this type with the specified name.
- valueOf(String) - Static method in enum org.deeplearning4j.earlystopping.scorecalc.ROCScoreCalculator.Metric
-
Returns the enum constant of this type with the specified name.
- valueOf(String) - Static method in enum org.deeplearning4j.earlystopping.scorecalc.ROCScoreCalculator.ROCType
-
Returns the enum constant of this type with the specified name.
- valueOf(String) - Static method in enum org.deeplearning4j.eval.Evaluation.Metric
-
Returns the enum constant of this type with the specified name.
- valueOf(String) - Static method in enum org.deeplearning4j.eval.EvaluationAveraging
-
Returns the enum constant of this type with the specified name.
- valueOf(String) - Static method in enum org.deeplearning4j.eval.RegressionEvaluation.Metric
-
Returns the enum constant of this type with the specified name.
- valueOf(String) - Static method in enum org.deeplearning4j.graph.api.NoEdgeHandling
-
Returns the enum constant of this type with the specified name.
- valueOf(String) - Static method in enum org.deeplearning4j.iterator.CnnSentenceDataSetIterator.UnknownWordHandling
-
Returns the enum constant of this type with the specified name.
- valueOf(String) - Static method in enum org.deeplearning4j.models.sequencevectors.enums.ListenerEvent
-
Returns the enum constant of this type with the specified name.
- valueOf(String) - Static method in enum org.deeplearning4j.models.sequencevectors.graph.enums.NoEdgeHandling
-
Returns the enum constant of this type with the specified name.
- valueOf(String) - Static method in enum org.deeplearning4j.models.sequencevectors.graph.enums.PopularityMode
-
Returns the enum constant of this type with the specified name.
- valueOf(String) - Static method in enum org.deeplearning4j.models.sequencevectors.graph.enums.SamplingMode
-
Returns the enum constant of this type with the specified name.
- valueOf(String) - Static method in enum org.deeplearning4j.models.sequencevectors.graph.enums.SpreadSpectrum
-
Returns the enum constant of this type with the specified name.
- valueOf(String) - Static method in enum org.deeplearning4j.models.sequencevectors.graph.enums.WalkDirection
-
Returns the enum constant of this type with the specified name.
- valueOf(String) - Static method in enum org.deeplearning4j.models.sequencevectors.graph.enums.WalkMode
-
Returns the enum constant of this type with the specified name.
- valueOf(String) - Static method in enum org.deeplearning4j.nn.api.FwdPassType
-
Returns the enum constant of this type with the specified name.
- valueOf(String) - Static method in enum org.deeplearning4j.nn.api.Layer.TrainingMode
-
Returns the enum constant of this type with the specified name.
- valueOf(String) - Static method in enum org.deeplearning4j.nn.api.Layer.Type
-
Returns the enum constant of this type with the specified name.
- valueOf(String) - Static method in enum org.deeplearning4j.nn.api.MaskState
-
Returns the enum constant of this type with the specified name.
- valueOf(String) - Static method in enum org.deeplearning4j.nn.api.OptimizationAlgorithm
-
Returns the enum constant of this type with the specified name.
- valueOf(String) - Static method in enum org.deeplearning4j.nn.conf.BackpropType
-
Returns the enum constant of this type with the specified name.
- valueOf(String) - Static method in enum org.deeplearning4j.nn.conf.CacheMode
-
Returns the enum constant of this type with the specified name.
- valueOf(String) - Static method in enum org.deeplearning4j.nn.conf.ConvolutionMode
-
Returns the enum constant of this type with the specified name.
- valueOf(String) - Static method in enum org.deeplearning4j.nn.conf.GradientNormalization
-
Returns the enum constant of this type with the specified name.
- valueOf(String) - Static method in enum org.deeplearning4j.nn.conf.graph.ElementWiseVertex.Op
-
Returns the enum constant of this type with the specified name.
- valueOf(String) - Static method in enum org.deeplearning4j.nn.conf.inputs.InputType.Type
-
Returns the enum constant of this type with the specified name.
- valueOf(String) - Static method in enum org.deeplearning4j.nn.conf.layers.Convolution3D.DataFormat
-
Returns the enum constant of this type with the specified name.
- valueOf(String) - Static method in enum org.deeplearning4j.nn.conf.layers.ConvolutionLayer.AlgoMode
-
Returns the enum constant of this type with the specified name.
- valueOf(String) - Static method in enum org.deeplearning4j.nn.conf.layers.ConvolutionLayer.BwdDataAlgo
-
Returns the enum constant of this type with the specified name.
- valueOf(String) - Static method in enum org.deeplearning4j.nn.conf.layers.ConvolutionLayer.BwdFilterAlgo
-
Returns the enum constant of this type with the specified name.
- valueOf(String) - Static method in enum org.deeplearning4j.nn.conf.layers.ConvolutionLayer.FwdAlgo
-
Returns the enum constant of this type with the specified name.
- valueOf(String) - Static method in enum org.deeplearning4j.nn.conf.layers.PoolingType
-
Returns the enum constant of this type with the specified name.
- valueOf(String) - Static method in enum org.deeplearning4j.nn.conf.layers.recurrent.Bidirectional.Mode
-
Returns the enum constant of this type with the specified name.
- valueOf(String) - Static method in enum org.deeplearning4j.nn.conf.layers.SpaceToDepthLayer.DataFormat
-
Returns the enum constant of this type with the specified name.
- valueOf(String) - Static method in enum org.deeplearning4j.nn.conf.layers.Subsampling3DLayer.PoolingType
-
Returns the enum constant of this type with the specified name.
- valueOf(String) - Static method in enum org.deeplearning4j.nn.conf.layers.SubsamplingLayer.PoolingType
-
Returns the enum constant of this type with the specified name.
- valueOf(String) - Static method in enum org.deeplearning4j.nn.conf.memory.MemoryType
-
Returns the enum constant of this type with the specified name.
- valueOf(String) - Static method in enum org.deeplearning4j.nn.conf.memory.MemoryUseMode
-
Returns the enum constant of this type with the specified name.
- valueOf(String) - Static method in enum org.deeplearning4j.nn.conf.Updater
-
Returns the enum constant of this type with the specified name.
- valueOf(String) - Static method in enum org.deeplearning4j.nn.conf.WorkspaceMode
-
Returns the enum constant of this type with the specified name.
- valueOf(String) - Static method in enum org.deeplearning4j.nn.graph.vertex.impl.ElementWiseVertex.Op
-
Returns the enum constant of this type with the specified name.
- valueOf(String) - Static method in enum org.deeplearning4j.nn.modelimport.keras.KerasLayer.DimOrder
-
Returns the enum constant of this type with the specified name.
- valueOf(String) - Static method in enum org.deeplearning4j.nn.weights.WeightInit
-
Returns the enum constant of this type with the specified name.
- valueOf(String) - Static method in enum org.deeplearning4j.nn.workspace.ArrayType
-
Returns the enum constant of this type with the specified name.
- valueOf(String) - Static method in enum org.deeplearning4j.optimize.api.InvocationType
-
Returns the enum constant of this type with the specified name.
- valueOf(String) - Static method in enum org.deeplearning4j.optimize.listeners.SleepyTrainingListener.SleepMode
-
Returns the enum constant of this type with the specified name.
- valueOf(String) - Static method in enum org.deeplearning4j.optimize.listeners.SleepyTrainingListener.TimeMode
-
Returns the enum constant of this type with the specified name.
- valueOf(String) - Static method in enum org.deeplearning4j.parallelism.inference.InferenceMode
-
Returns the enum constant of this type with the specified name.
- valueOf(String) - Static method in enum org.deeplearning4j.parallelism.MagicQueue.Mode
-
Deprecated.
Returns the enum constant of this type with the specified name.
- valueOf(String) - Static method in enum org.deeplearning4j.parallelism.MagicQueue.Type
-
Deprecated.
Returns the enum constant of this type with the specified name.
- valueOf(String) - Static method in enum org.deeplearning4j.parallelism.ParallelWrapper.TrainingMode
-
Returns the enum constant of this type with the specified name.
- valueOf(String) - Static method in enum org.deeplearning4j.spark.api.RDDTrainingApproach
-
Returns the enum constant of this type with the specified name.
- valueOf(String) - Static method in enum org.deeplearning4j.spark.api.Repartition
-
Returns the enum constant of this type with the specified name.
- valueOf(String) - Static method in enum org.deeplearning4j.spark.api.RepartitionStrategy
-
Returns the enum constant of this type with the specified name.
- valueOf(String) - Static method in enum org.deeplearning4j.spark.datavec.DataVecSequencePairDataSetFunction.AlignmentMode
-
Returns the enum constant of this type with the specified name.
- valueOf(String) - Static method in enum org.deeplearning4j.streaming.kafka.NDArrayType
-
Returns the enum constant of this type with the specified name.
- valueOf(String) - Static method in enum org.deeplearning4j.ui.api.FunctionType
-
Returns the enum constant of this type with the specified name.
- valueOf(String) - Static method in enum org.deeplearning4j.ui.api.HttpMethod
-
Returns the enum constant of this type with the specified name.
- valueOf(String) - Static method in enum org.deeplearning4j.ui.api.LengthUnit
-
Returns the enum constant of this type with the specified name.
- valueOf(String) - Static method in enum org.deeplearning4j.ui.components.component.style.StyleDiv.FloatValue
-
Returns the enum constant of this type with the specified name.
- valueOf(String) - Static method in enum org.deeplearning4j.ui.stats.api.StatsType
-
Returns the enum constant of this type with the specified name.
- valueOf(String) - Static method in enum org.deeplearning4j.ui.stats.api.SummaryType
-
Returns the enum constant of this type with the specified name.
- valueOf(String) - Static method in enum org.deeplearning4j.ui.stats.sbe.MemoryType
-
Returns the enum constant of this type with the specified name.
- valueOf(String) - Static method in enum org.deeplearning4j.ui.stats.sbe.MetaAttribute
-
Returns the enum constant of this type with the specified name.
- valueOf(String) - Static method in enum org.deeplearning4j.ui.stats.sbe.StatSource
-
Returns the enum constant of this type with the specified name.
- valueOf(String) - Static method in enum org.deeplearning4j.ui.stats.sbe.StatsType
-
Returns the enum constant of this type with the specified name.
- valueOf(String) - Static method in enum org.deeplearning4j.ui.stats.sbe.StatType
-
Returns the enum constant of this type with the specified name.
- valueOf(String) - Static method in enum org.deeplearning4j.ui.stats.sbe.SummaryType
-
Returns the enum constant of this type with the specified name.
- valueOf(String) - Static method in enum org.deeplearning4j.zoo.PretrainedType
-
Returns the enum constant of this type with the specified name.
- valueOf(String) - Static method in enum org.deeplearning4j.zoo.ZooType
-
Returns the enum constant of this type with the specified name.
- values() - Static method in enum com.atilika.kuromoji.TokenizerBase.Mode
-
Returns an array containing the constants of this enum type, in
the order they are declared.
- values() - Method in class com.atilika.kuromoji.trie.PatriciaTrie
-
Returns a copy of the values contained in this trie as a Set
- values() - Static method in enum com.atilika.kuromoji.viterbi.ViterbiNode.Type
-
Returns an array containing the constants of this enum type, in
the order they are declared.
- values() - Static method in enum org.ansj.util.TermUtil.InsertTermType
-
Returns an array containing the constants of this enum type, in
the order they are declared.
- values() - Static method in enum org.deeplearning4j.api.storage.StatsStorageListener.EventType
-
Returns an array containing the constants of this enum type, in
the order they are declared.
- values() - Static method in enum org.deeplearning4j.api.storage.StorageType
-
Returns an array containing the constants of this enum type, in
the order they are declared.
- values() - Static method in enum org.deeplearning4j.clustering.optimisation.ClusteringOptimizationType
-
Returns an array containing the constants of this enum type, in
the order they are declared.
- values() - Static method in enum org.deeplearning4j.clustering.strategy.ClusteringStrategyType
-
Returns an array containing the constants of this enum type, in
the order they are declared.
- values() - Static method in enum org.deeplearning4j.datasets.datavec.RecordReaderMultiDataSetIterator.AlignmentMode
-
Returns an array containing the constants of this enum type, in
the order they are declared.
- values() - Static method in enum org.deeplearning4j.datasets.datavec.SequenceRecordReaderDataSetIterator.AlignmentMode
-
Returns an array containing the constants of this enum type, in
the order they are declared.
- values() - Static method in enum org.deeplearning4j.datasets.fetchers.DataSetType
-
Returns an array containing the constants of this enum type, in
the order they are declared.
- values() - Static method in enum org.deeplearning4j.datasets.iterator.impl.EmnistDataSetIterator.Set
-
Returns an array containing the constants of this enum type, in
the order they are declared.
- values() - Static method in enum org.deeplearning4j.datasets.rearrange.LocalUnstructuredDataFormatter.LabelingType
-
Returns an array containing the constants of this enum type, in
the order they are declared.
- values() - Static method in enum org.deeplearning4j.earlystopping.EarlyStoppingResult.TerminationReason
-
Returns an array containing the constants of this enum type, in
the order they are declared.
- values() - Static method in enum org.deeplearning4j.earlystopping.scorecalc.ROCScoreCalculator.Metric
-
Returns an array containing the constants of this enum type, in
the order they are declared.
- values() - Static method in enum org.deeplearning4j.earlystopping.scorecalc.ROCScoreCalculator.ROCType
-
Returns an array containing the constants of this enum type, in
the order they are declared.
- values() - Static method in enum org.deeplearning4j.eval.Evaluation.Metric
-
Returns an array containing the constants of this enum type, in
the order they are declared.
- values() - Static method in enum org.deeplearning4j.eval.EvaluationAveraging
-
Returns an array containing the constants of this enum type, in
the order they are declared.
- values() - Static method in enum org.deeplearning4j.eval.RegressionEvaluation.Metric
-
Returns an array containing the constants of this enum type, in
the order they are declared.
- values() - Static method in enum org.deeplearning4j.graph.api.NoEdgeHandling
-
Returns an array containing the constants of this enum type, in
the order they are declared.
- values() - Static method in enum org.deeplearning4j.iterator.CnnSentenceDataSetIterator.UnknownWordHandling
-
Returns an array containing the constants of this enum type, in
the order they are declared.
- values() - Static method in enum org.deeplearning4j.models.sequencevectors.enums.ListenerEvent
-
Returns an array containing the constants of this enum type, in
the order they are declared.
- values() - Static method in enum org.deeplearning4j.models.sequencevectors.graph.enums.NoEdgeHandling
-
Returns an array containing the constants of this enum type, in
the order they are declared.
- values() - Static method in enum org.deeplearning4j.models.sequencevectors.graph.enums.PopularityMode
-
Returns an array containing the constants of this enum type, in
the order they are declared.
- values() - Static method in enum org.deeplearning4j.models.sequencevectors.graph.enums.SamplingMode
-
Returns an array containing the constants of this enum type, in
the order they are declared.
- values() - Static method in enum org.deeplearning4j.models.sequencevectors.graph.enums.SpreadSpectrum
-
Returns an array containing the constants of this enum type, in
the order they are declared.
- values() - Static method in enum org.deeplearning4j.models.sequencevectors.graph.enums.WalkDirection
-
Returns an array containing the constants of this enum type, in
the order they are declared.
- values() - Static method in enum org.deeplearning4j.models.sequencevectors.graph.enums.WalkMode
-
Returns an array containing the constants of this enum type, in
the order they are declared.
- values() - Static method in enum org.deeplearning4j.nn.api.FwdPassType
-
Returns an array containing the constants of this enum type, in
the order they are declared.
- values() - Static method in enum org.deeplearning4j.nn.api.Layer.TrainingMode
-
Returns an array containing the constants of this enum type, in
the order they are declared.
- values() - Static method in enum org.deeplearning4j.nn.api.Layer.Type
-
Returns an array containing the constants of this enum type, in
the order they are declared.
- values() - Static method in enum org.deeplearning4j.nn.api.MaskState
-
Returns an array containing the constants of this enum type, in
the order they are declared.
- values() - Static method in enum org.deeplearning4j.nn.api.OptimizationAlgorithm
-
Returns an array containing the constants of this enum type, in
the order they are declared.
- values() - Static method in enum org.deeplearning4j.nn.conf.BackpropType
-
Returns an array containing the constants of this enum type, in
the order they are declared.
- values() - Static method in enum org.deeplearning4j.nn.conf.CacheMode
-
Returns an array containing the constants of this enum type, in
the order they are declared.
- values() - Static method in enum org.deeplearning4j.nn.conf.ConvolutionMode
-
Returns an array containing the constants of this enum type, in
the order they are declared.
- values() - Static method in enum org.deeplearning4j.nn.conf.GradientNormalization
-
Returns an array containing the constants of this enum type, in
the order they are declared.
- values() - Static method in enum org.deeplearning4j.nn.conf.graph.ElementWiseVertex.Op
-
Returns an array containing the constants of this enum type, in
the order they are declared.
- values() - Static method in enum org.deeplearning4j.nn.conf.inputs.InputType.Type
-
Returns an array containing the constants of this enum type, in
the order they are declared.
- values() - Static method in enum org.deeplearning4j.nn.conf.layers.Convolution3D.DataFormat
-
Returns an array containing the constants of this enum type, in
the order they are declared.
- values() - Static method in enum org.deeplearning4j.nn.conf.layers.ConvolutionLayer.AlgoMode
-
Returns an array containing the constants of this enum type, in
the order they are declared.
- values() - Static method in enum org.deeplearning4j.nn.conf.layers.ConvolutionLayer.BwdDataAlgo
-
Returns an array containing the constants of this enum type, in
the order they are declared.
- values() - Static method in enum org.deeplearning4j.nn.conf.layers.ConvolutionLayer.BwdFilterAlgo
-
Returns an array containing the constants of this enum type, in
the order they are declared.
- values() - Static method in enum org.deeplearning4j.nn.conf.layers.ConvolutionLayer.FwdAlgo
-
Returns an array containing the constants of this enum type, in
the order they are declared.
- values() - Static method in enum org.deeplearning4j.nn.conf.layers.PoolingType
-
Returns an array containing the constants of this enum type, in
the order they are declared.
- values() - Static method in enum org.deeplearning4j.nn.conf.layers.recurrent.Bidirectional.Mode
-
Returns an array containing the constants of this enum type, in
the order they are declared.
- values() - Static method in enum org.deeplearning4j.nn.conf.layers.SpaceToDepthLayer.DataFormat
-
Returns an array containing the constants of this enum type, in
the order they are declared.
- values() - Static method in enum org.deeplearning4j.nn.conf.layers.Subsampling3DLayer.PoolingType
-
Returns an array containing the constants of this enum type, in
the order they are declared.
- values() - Static method in enum org.deeplearning4j.nn.conf.layers.SubsamplingLayer.PoolingType
-
Returns an array containing the constants of this enum type, in
the order they are declared.
- values() - Static method in enum org.deeplearning4j.nn.conf.memory.MemoryType
-
Returns an array containing the constants of this enum type, in
the order they are declared.
- values() - Static method in enum org.deeplearning4j.nn.conf.memory.MemoryUseMode
-
Returns an array containing the constants of this enum type, in
the order they are declared.
- values() - Static method in enum org.deeplearning4j.nn.conf.Updater
-
Returns an array containing the constants of this enum type, in
the order they are declared.
- values() - Static method in enum org.deeplearning4j.nn.conf.WorkspaceMode
-
Returns an array containing the constants of this enum type, in
the order they are declared.
- values() - Static method in enum org.deeplearning4j.nn.graph.vertex.impl.ElementWiseVertex.Op
-
Returns an array containing the constants of this enum type, in
the order they are declared.
- values() - Static method in enum org.deeplearning4j.nn.modelimport.keras.KerasLayer.DimOrder
-
Returns an array containing the constants of this enum type, in
the order they are declared.
- values() - Static method in enum org.deeplearning4j.nn.weights.WeightInit
-
Returns an array containing the constants of this enum type, in
the order they are declared.
- values() - Static method in enum org.deeplearning4j.nn.workspace.ArrayType
-
Returns an array containing the constants of this enum type, in
the order they are declared.
- values() - Static method in enum org.deeplearning4j.optimize.api.InvocationType
-
Returns an array containing the constants of this enum type, in
the order they are declared.
- values() - Static method in enum org.deeplearning4j.optimize.listeners.SleepyTrainingListener.SleepMode
-
Returns an array containing the constants of this enum type, in
the order they are declared.
- values() - Static method in enum org.deeplearning4j.optimize.listeners.SleepyTrainingListener.TimeMode
-
Returns an array containing the constants of this enum type, in
the order they are declared.
- values() - Static method in enum org.deeplearning4j.parallelism.inference.InferenceMode
-
Returns an array containing the constants of this enum type, in
the order they are declared.
- values() - Static method in enum org.deeplearning4j.parallelism.MagicQueue.Mode
-
Deprecated.
Returns an array containing the constants of this enum type, in
the order they are declared.
- values() - Static method in enum org.deeplearning4j.parallelism.MagicQueue.Type
-
Deprecated.
Returns an array containing the constants of this enum type, in
the order they are declared.
- values() - Static method in enum org.deeplearning4j.parallelism.ParallelWrapper.TrainingMode
-
Returns an array containing the constants of this enum type, in
the order they are declared.
- values() - Static method in enum org.deeplearning4j.spark.api.RDDTrainingApproach
-
Returns an array containing the constants of this enum type, in
the order they are declared.
- values() - Static method in enum org.deeplearning4j.spark.api.Repartition
-
Returns an array containing the constants of this enum type, in
the order they are declared.
- values() - Static method in enum org.deeplearning4j.spark.api.RepartitionStrategy
-
Returns an array containing the constants of this enum type, in
the order they are declared.
- values() - Static method in enum org.deeplearning4j.spark.datavec.DataVecSequencePairDataSetFunction.AlignmentMode
-
Returns an array containing the constants of this enum type, in
the order they are declared.
- values() - Static method in enum org.deeplearning4j.streaming.kafka.NDArrayType
-
Returns an array containing the constants of this enum type, in
the order they are declared.
- values() - Static method in enum org.deeplearning4j.ui.api.FunctionType
-
Returns an array containing the constants of this enum type, in
the order they are declared.
- values() - Static method in enum org.deeplearning4j.ui.api.HttpMethod
-
Returns an array containing the constants of this enum type, in
the order they are declared.
- values() - Static method in enum org.deeplearning4j.ui.api.LengthUnit
-
Returns an array containing the constants of this enum type, in
the order they are declared.
- values() - Static method in enum org.deeplearning4j.ui.components.component.style.StyleDiv.FloatValue
-
Returns an array containing the constants of this enum type, in
the order they are declared.
- values() - Static method in enum org.deeplearning4j.ui.stats.api.StatsType
-
Returns an array containing the constants of this enum type, in
the order they are declared.
- values() - Static method in enum org.deeplearning4j.ui.stats.api.SummaryType
-
Returns an array containing the constants of this enum type, in
the order they are declared.
- values() - Static method in enum org.deeplearning4j.ui.stats.sbe.MemoryType
-
Returns an array containing the constants of this enum type, in
the order they are declared.
- values() - Static method in enum org.deeplearning4j.ui.stats.sbe.MetaAttribute
-
Returns an array containing the constants of this enum type, in
the order they are declared.
- values() - Static method in enum org.deeplearning4j.ui.stats.sbe.StatSource
-
Returns an array containing the constants of this enum type, in
the order they are declared.
- values() - Static method in enum org.deeplearning4j.ui.stats.sbe.StatsType
-
Returns an array containing the constants of this enum type, in
the order they are declared.
- values() - Static method in enum org.deeplearning4j.ui.stats.sbe.StatType
-
Returns an array containing the constants of this enum type, in
the order they are declared.
- values() - Static method in enum org.deeplearning4j.ui.stats.sbe.SummaryType
-
Returns an array containing the constants of this enum type, in
the order they are declared.
- values() - Static method in enum org.deeplearning4j.zoo.PretrainedType
-
Returns an array containing the constants of this enum type, in
the order they are declared.
- values() - Static method in enum org.deeplearning4j.zoo.ZooType
-
Returns an array containing the constants of this enum type, in
the order they are declared.
- VanillaStatsStorageRouter - Class in org.deeplearning4j.spark.impl.listeners
-
Standard router for use in Spark: simply collect the data for later serialization and passing back to the master.
- VanillaStatsStorageRouter() - Constructor for class org.deeplearning4j.spark.impl.listeners.VanillaStatsStorageRouter
-
- VanillaStatsStorageRouterProvider - Class in org.deeplearning4j.spark.impl.listeners
-
- VanillaStatsStorageRouterProvider() - Constructor for class org.deeplearning4j.spark.impl.listeners.VanillaStatsStorageRouterProvider
-
- varDataMaxValue() - Static method in class org.deeplearning4j.ui.stats.sbe.VarDataUTF8Decoder
-
- varDataMaxValue() - Static method in class org.deeplearning4j.ui.stats.sbe.VarDataUTF8Encoder
-
- varDataMinValue() - Static method in class org.deeplearning4j.ui.stats.sbe.VarDataUTF8Decoder
-
- varDataMinValue() - Static method in class org.deeplearning4j.ui.stats.sbe.VarDataUTF8Encoder
-
- varDataNullValue() - Static method in class org.deeplearning4j.ui.stats.sbe.VarDataUTF8Decoder
-
- varDataNullValue() - Static method in class org.deeplearning4j.ui.stats.sbe.VarDataUTF8Encoder
-
- VarDataUTF8Decoder - Class in org.deeplearning4j.ui.stats.sbe
-
- VarDataUTF8Decoder() - Constructor for class org.deeplearning4j.ui.stats.sbe.VarDataUTF8Decoder
-
- VarDataUTF8Encoder - Class in org.deeplearning4j.ui.stats.sbe
-
- VarDataUTF8Encoder() - Constructor for class org.deeplearning4j.ui.stats.sbe.VarDataUTF8Encoder
-
- variables - Variable in class org.deeplearning4j.nn.conf.NeuralNetConfiguration
-
- variables() - Method in class org.deeplearning4j.nn.conf.NeuralNetConfiguration
-
- variables(boolean) - Method in class org.deeplearning4j.nn.conf.NeuralNetConfiguration
-
- variableWindows - Variable in class org.deeplearning4j.models.embeddings.learning.impl.elements.CBOW
-
- variableWindows - Variable in class org.deeplearning4j.models.embeddings.learning.impl.elements.SkipGram
-
- variableWindows - Variable in class org.deeplearning4j.models.embeddings.wordvectors.WordVectorsImpl
-
- variableWindows - Variable in class org.deeplearning4j.models.sequencevectors.SequenceVectors.Builder
-
- variance(double[]) - Static method in class org.deeplearning4j.clustering.util.MathUtils
-
- VarianceVariationCondition - Class in org.deeplearning4j.clustering.condition
-
- VarianceVariationCondition() - Constructor for class org.deeplearning4j.clustering.condition.VarianceVariationCondition
-
- varianceVariationLessThan(double, int) - Static method in class org.deeplearning4j.clustering.condition.VarianceVariationCondition
-
- VariationalAutoencoder - Class in org.deeplearning4j.nn.conf.layers.variational
-
Variational Autoencoder layer
- VariationalAutoencoder - Class in org.deeplearning4j.nn.layers.variational
-
Variational Autoencoder layer
- VariationalAutoencoder(NeuralNetConfiguration) - Constructor for class org.deeplearning4j.nn.layers.variational.VariationalAutoencoder
-
- VariationalAutoencoder.Builder - Class in org.deeplearning4j.nn.conf.layers.variational
-
- VariationalAutoencoderParamInitializer - Class in org.deeplearning4j.nn.params
-
Parameter initializer for the Variational Autoencoder model.
- VariationalAutoencoderParamInitializer() - Constructor for class org.deeplearning4j.nn.params.VariationalAutoencoderParamInitializer
-
- vector(String) - Method in class org.deeplearning4j.models.embeddings.inmemory.InMemoryLookupTable
-
- vector(String) - Method in interface org.deeplearning4j.models.embeddings.WeightLookupTable
-
- vector() - Method in class org.deeplearning4j.nn.layers.feedforward.autoencoder.recursive.Tree
-
- VECTOR_LENGTH - Static variable in class org.deeplearning4j.spark.models.embeddings.glove.GlovePerformer
-
- VECTOR_LENGTH - Static variable in class org.deeplearning4j.spark.models.embeddings.word2vec.Word2VecPerformerVoid
-
Deprecated.
- VECTOR_LENGTH - Static variable in class org.deeplearning4j.spark.models.embeddings.word2vec.Word2VecVariables
-
Deprecated.
- vectorize(InputStream, String) - Method in class org.deeplearning4j.bagofwords.vectorizer.BagOfWordsVectorizer
-
Text coming from an input stream considered as one document
- vectorize(String, String) - Method in class org.deeplearning4j.bagofwords.vectorizer.BagOfWordsVectorizer
-
- vectorize(File, String) - Method in class org.deeplearning4j.bagofwords.vectorizer.BagOfWordsVectorizer
-
- vectorize() - Method in class org.deeplearning4j.bagofwords.vectorizer.BagOfWordsVectorizer
-
Vectorizes the input source in to a dataset
- vectorize(InputStream, String) - Method in interface org.deeplearning4j.bagofwords.vectorizer.TextVectorizer
-
Text coming from an input stream considered as one document
- vectorize(String, String) - Method in interface org.deeplearning4j.bagofwords.vectorizer.TextVectorizer
-
Vectorizes the passed in text treating it as one document
- vectorize(File, String) - Method in interface org.deeplearning4j.bagofwords.vectorizer.TextVectorizer
-
- vectorize(InputStream, String) - Method in class org.deeplearning4j.bagofwords.vectorizer.TfidfVectorizer
-
Text coming from an input stream considered as one document
- vectorize(String, String) - Method in class org.deeplearning4j.bagofwords.vectorizer.TfidfVectorizer
-
Vectorizes the passed in text treating it as one document
- vectorize(File, String) - Method in class org.deeplearning4j.bagofwords.vectorizer.TfidfVectorizer
-
- vectorize() - Method in class org.deeplearning4j.bagofwords.vectorizer.TfidfVectorizer
-
Vectorizes the input source in to a dataset
- vectorize() - Method in interface org.deeplearning4j.datasets.vectorizer.Vectorizer
-
Vectorizes the input source in to a dataset
- Vectorizer - Interface in org.deeplearning4j.datasets.vectorizer
-
A Vectorizer at its essence takes an input source
and converts it to a matrix for neural network consumption.
- vectorLength(double[]) - Static method in class org.deeplearning4j.clustering.util.MathUtils
-
Returns the vector length (sqrt(sum(x_i))
- vectorLength - Variable in class org.deeplearning4j.models.embeddings.inmemory.InMemoryLookupTable.Builder
-
- vectorLength(int) - Method in class org.deeplearning4j.models.embeddings.inmemory.InMemoryLookupTable.Builder
-
- vectorLength - Variable in class org.deeplearning4j.models.embeddings.inmemory.InMemoryLookupTable
-
- vectorLength - Variable in class org.deeplearning4j.models.embeddings.learning.impl.elements.SkipGram
-
- vectorLength - Variable in class org.deeplearning4j.models.embeddings.loader.WordVectorSerializer.BinaryReader
-
- vectorLength(int) - Method in class org.deeplearning4j.models.glove.GloveWeightLookupTable.Builder
-
Deprecated.
- vectorLength(int) - Method in class org.deeplearning4j.spark.models.embeddings.glove.GloveParam.Builder
-
- vectors() - Method in class org.deeplearning4j.models.embeddings.inmemory.InMemoryLookupTable
-
- vectors() - Method in interface org.deeplearning4j.models.embeddings.WeightLookupTable
-
Iterates through all of the vectors in the cache
- vectorsAndGradients(int, int) - Method in class org.deeplearning4j.graph.models.embeddings.InMemoryGraphLookupTable
-
Returns vertex vector and vector gradients, plus inner node vectors and inner node gradients
Specifically, out[0] are vectors, out[1] are gradients for the corresponding vectors
out[0][0] is vector for first vertex; out[0][1] is gradient for this vertex vector
out[0][i] (i>0) is the inner node vector along path to second vertex; out[1][i] is gradient for inner node vertex
This design is used primarily to aid in testing (numerical gradient checks)
- VectorsConfiguration - Class in org.deeplearning4j.models.embeddings.loader
-
This is simple bean/POJO for Word2Vec persistence handling.
- VectorsConfiguration() - Constructor for class org.deeplearning4j.models.embeddings.loader.VectorsConfiguration
-
- vectorsConfiguration - Variable in class org.deeplearning4j.spark.models.sequencevectors.functions.PartitionTrainingFunction
-
- vectorsConfiguration - Variable in class org.deeplearning4j.spark.models.sequencevectors.functions.TrainingFunction
-
- vectorsConfiguration - Variable in class org.deeplearning4j.spark.models.sequencevectors.learning.elements.BaseSparkLearningAlgorithm
-
- vectorsConfiguration - Variable in class org.deeplearning4j.spark.models.sequencevectors.learning.sequence.BaseSparkSequenceLearningAlgorithm
-
- vectorsConfigurationBroadcast - Variable in class org.deeplearning4j.spark.models.sequencevectors.functions.CountFunction
-
- vectorsConfigurationBroadcast - Variable in class org.deeplearning4j.spark.models.sequencevectors.functions.DistributedFunction
-
- vectorSize(int) - Method in class org.deeplearning4j.graph.models.deepwalk.DeepWalk.Builder
-
Sets the size of the vectors to be learned for each vertex in the graph
- vectorSize() - Method in interface org.deeplearning4j.graph.models.embeddings.GraphVectorLookupTable
-
The size of the vector representations
- vectorSize - Variable in class org.deeplearning4j.graph.models.embeddings.InMemoryGraphLookupTable
-
- vectorSize() - Method in class org.deeplearning4j.graph.models.embeddings.InMemoryGraphLookupTable
-
- VectorsListener<T extends SequenceElement> - Interface in org.deeplearning4j.models.sequencevectors.interfaces
-
This interface describes Listeners to SequenceVectors and its derivatives.
- vectorsListeners - Variable in class org.deeplearning4j.models.sequencevectors.SequenceVectors.Builder
-
- VERSION - Static variable in class org.ansj.app.crf.model.CRFModel
-
- version() - Method in class org.deeplearning4j.ui.stats.sbe.MessageHeaderDecoder
-
- version(int) - Method in class org.deeplearning4j.ui.stats.sbe.MessageHeaderEncoder
-
- versionMaxValue() - Static method in class org.deeplearning4j.ui.stats.sbe.MessageHeaderDecoder
-
- versionMaxValue() - Static method in class org.deeplearning4j.ui.stats.sbe.MessageHeaderEncoder
-
- versionMinValue() - Static method in class org.deeplearning4j.ui.stats.sbe.MessageHeaderDecoder
-
- versionMinValue() - Static method in class org.deeplearning4j.ui.stats.sbe.MessageHeaderEncoder
-
- versionNullValue() - Static method in class org.deeplearning4j.ui.stats.sbe.MessageHeaderDecoder
-
- versionNullValue() - Static method in class org.deeplearning4j.ui.stats.sbe.MessageHeaderEncoder
-
- Vertex<T> - Class in org.deeplearning4j.graph.api
-
Vertex in a graph
- Vertex() - Constructor for class org.deeplearning4j.graph.api.Vertex
-
- Vertex<T extends SequenceElement> - Class in org.deeplearning4j.models.sequencevectors.graph.primitives
-
Vertex in a graph
- Vertex() - Constructor for class org.deeplearning4j.models.sequencevectors.graph.primitives.Vertex
-
- vertex - Variable in class org.deeplearning4j.nn.modelimport.keras.KerasLayer
-
- VertexComparator(IGraph<V, E>) - Constructor for class org.deeplearning4j.models.sequencevectors.graph.walkers.impl.NearestVertexWalker.VertexComparator
-
- VertexFactory<T> - Interface in org.deeplearning4j.graph.vertexfactory
-
Vertex factory, used to create nodes from an integer index (0 to nVertices-1 inclusive)
- VertexFactory<T extends SequenceElement> - Interface in org.deeplearning4j.models.sequencevectors.graph.vertex
-
Vertex factory, used to create nodes from an integer index (0 to nVertices-1 inclusive)
- vertexID() - Method in class org.deeplearning4j.graph.api.Vertex
-
- vertexID() - Method in class org.deeplearning4j.models.sequencevectors.graph.primitives.Vertex
-
- vertexIndex - Variable in class org.deeplearning4j.nn.graph.vertex.BaseGraphVertex
-
The index of this vertex
- VertexIndices - Class in org.deeplearning4j.nn.graph.vertex
-
VertexIndices defines a pair of integers: the index of a vertex, and the edge number of that vertex.
- VertexIndices() - Constructor for class org.deeplearning4j.nn.graph.vertex.VertexIndices
-
- vertexInputs - Variable in class org.deeplearning4j.nn.conf.ComputationGraphConfiguration.GraphBuilder
-
Key: graph node.
- vertexInputs - Variable in class org.deeplearning4j.nn.conf.ComputationGraphConfiguration
-
- VertexLoader<V> - Interface in org.deeplearning4j.graph.data
-
Interface defines a method of leading vertices from a file.
- vertexName - Variable in class org.deeplearning4j.nn.graph.vertex.BaseGraphVertex
-
- VertexSequence<V> - Class in org.deeplearning4j.graph.graph
-
A vertex sequence represents a sequences of vertices in a graph
- VertexSequence(IGraph<V, ?>, int[]) - Constructor for class org.deeplearning4j.graph.graph.VertexSequence
-
- vertexVectors - Variable in class org.deeplearning4j.graph.models.embeddings.InMemoryGraphLookupTable
-
- vertices - Variable in class org.deeplearning4j.nn.conf.ComputationGraphConfiguration.GraphBuilder
-
- vertices - Variable in class org.deeplearning4j.nn.conf.ComputationGraphConfiguration
-
- vertices - Variable in class org.deeplearning4j.nn.graph.ComputationGraph
-
All GraphVertex objects in the network.
- verticesMap - Variable in class org.deeplearning4j.nn.graph.ComputationGraph
-
Map of vertices by name
- verticesNearest(int, int) - Method in class org.deeplearning4j.graph.models.embeddings.GraphVectorsImpl
-
- verticesNearest(int, int) - Method in interface org.deeplearning4j.graph.models.GraphVectors
-
- VGG16 - Class in org.deeplearning4j.zoo.model
-
VGG-16, from Very Deep Convolutional Networks for Large-Scale Image Recognition
https://arxiv.org/abs/1409.1556
Deep Face Recognition
http://www.robots.ox.ac.uk/~vgg/publications/2015/Parkhi15/parkhi15.pdf
- VGG19 - Class in org.deeplearning4j.zoo.model
-
VGG-19, from Very Deep Convolutional Networks for Large-Scale Image Recognition
https://arxiv.org/abs/1409.1556)
- VirtualDataSetIterator - Class in org.deeplearning4j.spark.parameterserver.iterators
-
This DataSetIterator implementation does accumulation of DataSets from different Spark executors, wrt Thread/Device Affinity
- VirtualDataSetIterator(List<Iterator<DataSet>>) - Constructor for class org.deeplearning4j.spark.parameterserver.iterators.VirtualDataSetIterator
-
- VirtualIterator<E> - Class in org.deeplearning4j.spark.parameterserver.iterators
-
This class is thin wrapper, to provide block-until-depleted functionality in multi-threaded environment
- VirtualIterator(Iterator<E>) - Constructor for class org.deeplearning4j.spark.parameterserver.iterators.VirtualIterator
-
- VirtualMultiDataSetIterator - Class in org.deeplearning4j.spark.parameterserver.iterators
-
This MultiDataSetIterator implementation does accumulation of MultiDataSets from different Spark executors, wrt Thread/Device Affinity
- VirtualMultiDataSetIterator(List<Iterator<MultiDataSet>>) - Constructor for class org.deeplearning4j.spark.parameterserver.iterators.VirtualMultiDataSetIterator
-
- VISIBLE_BIAS_KEY - Static variable in class org.deeplearning4j.nn.params.PretrainParamInitializer
-
- visibleBiasInit - Variable in class org.deeplearning4j.nn.conf.layers.BasePretrainNetwork.Builder
-
- visibleBiasInit(double) - Method in class org.deeplearning4j.nn.conf.layers.BasePretrainNetwork.Builder
-
- visibleBiasInit - Variable in class org.deeplearning4j.nn.conf.layers.BasePretrainNetwork
-
- ViterbiBuilder - Class in com.atilika.kuromoji.viterbi
-
- ViterbiBuilder(DoubleArrayTrie, TokenInfoDictionary, UnknownDictionary, UserDictionary, TokenizerBase.Mode) - Constructor for class com.atilika.kuromoji.viterbi.ViterbiBuilder
-
Constructor
- ViterbiFormatter - Class in com.atilika.kuromoji.viterbi
-
- ViterbiFormatter(ConnectionCosts) - Constructor for class com.atilika.kuromoji.viterbi.ViterbiFormatter
-
- ViterbiLattice - Class in com.atilika.kuromoji.viterbi
-
- ViterbiLattice(int) - Constructor for class com.atilika.kuromoji.viterbi.ViterbiLattice
-
- ViterbiNode - Class in com.atilika.kuromoji.viterbi
-
- ViterbiNode(int, String, int, int, int, int, ViterbiNode.Type) - Constructor for class com.atilika.kuromoji.viterbi.ViterbiNode
-
- ViterbiNode(int, String, Dictionary, int, ViterbiNode.Type) - Constructor for class com.atilika.kuromoji.viterbi.ViterbiNode
-
- ViterbiNode.Type - Enum in com.atilika.kuromoji.viterbi
-
- ViterbiSearcher - Class in com.atilika.kuromoji.viterbi
-
- ViterbiSearcher(TokenizerBase.Mode, ConnectionCosts, UnknownDictionary, List<Integer>) - Constructor for class com.atilika.kuromoji.viterbi.ViterbiSearcher
-
- vocab - Variable in class org.deeplearning4j.models.embeddings.inmemory.InMemoryLookupTable
-
- vocab() - Method in interface org.deeplearning4j.models.embeddings.wordvectors.WordVectors
-
Vocab for the vectors
- vocab - Variable in class org.deeplearning4j.models.embeddings.wordvectors.WordVectorsImpl
-
- vocab() - Method in class org.deeplearning4j.models.embeddings.wordvectors.WordVectorsImpl
-
- vocab() - Method in class org.deeplearning4j.models.word2vec.StaticWord2Vec
-
Vocab for the vectors
- vocabCache - Variable in class org.deeplearning4j.bagofwords.vectorizer.BagOfWordsVectorizer.Builder
-
- vocabCache - Variable in class org.deeplearning4j.bagofwords.vectorizer.BaseTextVectorizer
-
- vocabCache - Variable in class org.deeplearning4j.bagofwords.vectorizer.TfidfVectorizer.Builder
-
- vocabCache - Variable in class org.deeplearning4j.models.embeddings.inmemory.InMemoryLookupTable.Builder
-
- vocabCache - Variable in class org.deeplearning4j.models.embeddings.learning.impl.elements.SkipGram
-
- vocabCache - Variable in class org.deeplearning4j.models.embeddings.learning.impl.sequence.DBOW
-
- vocabCache - Variable in class org.deeplearning4j.models.embeddings.reader.impl.BasicModelUtils
-
- vocabCache - Variable in class org.deeplearning4j.models.glove.AbstractCoOccurrences.Builder
-
- vocabCache(VocabCache<T>) - Method in class org.deeplearning4j.models.glove.AbstractCoOccurrences.Builder
-
- vocabCache - Variable in class org.deeplearning4j.models.glove.AbstractCoOccurrences
-
- vocabCache(VocabCache<VocabWord>) - Method in class org.deeplearning4j.models.glove.Glove.Builder
-
- vocabCache(VocabCache<V>) - Method in class org.deeplearning4j.models.node2vec.Node2Vec.Builder
-
Deprecated.
- vocabCache(VocabCache<VocabWord>) - Method in class org.deeplearning4j.models.paragraphvectors.ParagraphVectors.Builder
-
This method allows to define external VocabCache to be used
- vocabCache - Variable in class org.deeplearning4j.models.sequencevectors.SequenceVectors.Builder
-
- vocabCache(VocabCache<T>) - Method in class org.deeplearning4j.models.sequencevectors.SequenceVectors.Builder
-
You can pass externally built vocabCache object, containing vocabulary
- vocabCache - Variable in class org.deeplearning4j.models.sequencevectors.transformers.impl.GraphTransformer.Builder
-
- vocabCache - Variable in class org.deeplearning4j.models.sequencevectors.transformers.impl.GraphTransformer
-
- vocabCache - Variable in class org.deeplearning4j.models.sequencevectors.transformers.impl.SentenceTransformer.Builder
-
- vocabCache(VocabCache<VocabWord>) - Method in class org.deeplearning4j.models.word2vec.Word2Vec.Builder
-
This method allows to define external VocabCache to be used
- VocabCache<T extends SequenceElement> - Interface in org.deeplearning4j.models.word2vec.wordstore
-
A VocabCache handles the storage of information needed for the word2vec look up table.
- vocabCache - Variable in class org.deeplearning4j.spark.models.sequencevectors.export.impl.VocabCacheExporter
-
- vocabCache - Variable in class org.deeplearning4j.spark.models.sequencevectors.learning.elements.BaseSparkLearningAlgorithm
-
- vocabCache - Variable in class org.deeplearning4j.spark.models.sequencevectors.learning.sequence.BaseSparkSequenceLearningAlgorithm
-
- vocabCacheBroadcast - Variable in class org.deeplearning4j.spark.models.sequencevectors.functions.PartitionTrainingFunction
-
- vocabCacheBroadcast - Variable in class org.deeplearning4j.spark.models.sequencevectors.functions.TrainingFunction
-
- vocabCacheBroadcast - Variable in class org.deeplearning4j.spark.models.sequencevectors.SparkSequenceVectors
-
- VocabCacheExporter - Class in org.deeplearning4j.spark.models.sequencevectors.export.impl
-
This model exporter is suitable for debug/testing only.
- VocabCacheExporter() - Constructor for class org.deeplearning4j.spark.models.sequencevectors.export.impl.VocabCacheExporter
-
- VocabConstructor<T extends SequenceElement> - Class in org.deeplearning4j.models.word2vec.wordstore
-
This class can be used to build joint vocabulary from special sources, that should be treated separately.
- VocabConstructor.Builder<T extends SequenceElement> - Class in org.deeplearning4j.models.word2vec.wordstore
-
- VocabConstructor.VocabRunnable - Class in org.deeplearning4j.models.word2vec.wordstore
-
- vocabExists() - Method in class org.deeplearning4j.models.word2vec.wordstore.inmemory.AbstractCache
-
Returns true, if number of elements in vocabulary > 0, false otherwise
- vocabExists() - Method in class org.deeplearning4j.models.word2vec.wordstore.inmemory.InMemoryLookupCache
-
Deprecated.
- vocabExists() - Method in interface org.deeplearning4j.models.word2vec.wordstore.VocabCache
-
Vocab exists already
- VocabHolder - Class in org.deeplearning4j.spark.models.embeddings.word2vec
-
- vocabId - Variable in class org.deeplearning4j.models.word2vec.VocabWord
-
- vocabLimit - Variable in class org.deeplearning4j.models.sequencevectors.SequenceVectors.Builder
-
- vocabLimit - Variable in class org.deeplearning4j.models.sequencevectors.SequenceVectors
-
- VocabRddFunctionFlat<T extends SequenceElement> - Class in org.deeplearning4j.spark.models.sequencevectors.functions
-
- VocabRddFunctionFlat(Broadcast<VectorsConfiguration>, Broadcast<VoidConfiguration>) - Constructor for class org.deeplearning4j.spark.models.sequencevectors.functions.VocabRddFunctionFlat
-
- VocabRunnable(AbstractCache<T>, Sequence<T>, AtomicLong, AtomicLong) - Constructor for class org.deeplearning4j.models.word2vec.wordstore.VocabConstructor.VocabRunnable
-
- vocabs - Variable in class org.deeplearning4j.models.word2vec.wordstore.inmemory.InMemoryLookupCache
-
Deprecated.
- VocabularyHolder - Class in org.deeplearning4j.models.word2vec.wordstore
-
This class is used as simplifed VocabCache for vocabulary building routines.
- VocabularyHolder() - Constructor for class org.deeplearning4j.models.word2vec.wordstore.VocabularyHolder
-
Default constructor
- VocabularyHolder(VocabCache<? extends SequenceElement>, boolean) - Constructor for class org.deeplearning4j.models.word2vec.wordstore.VocabularyHolder
-
Builds VocabularyHolder from VocabCache.
- VocabularyHolder.Builder - Class in org.deeplearning4j.models.word2vec.wordstore
-
- VocabularyWord - Class in org.deeplearning4j.models.word2vec.wordstore
-
Simplified version of VocabWord.
- VocabularyWord() - Constructor for class org.deeplearning4j.models.word2vec.wordstore.VocabularyWord
-
- VocabularyWord(String) - Constructor for class org.deeplearning4j.models.word2vec.wordstore.VocabularyWord
-
- VocabWord - Class in org.deeplearning4j.models.word2vec
-
Intermediate layers of the neural network
- VocabWord(double, String) - Constructor for class org.deeplearning4j.models.word2vec.VocabWord
-
- VocabWord(double, String, long) - Constructor for class org.deeplearning4j.models.word2vec.VocabWord
-
- VocabWord() - Constructor for class org.deeplearning4j.models.word2vec.VocabWord
-
- VocabWordFactory - Class in org.deeplearning4j.models.sequencevectors.serialization
-
- VocabWordFactory() - Constructor for class org.deeplearning4j.models.sequencevectors.serialization.VocabWordFactory
-
- VocabWordPairs - Class in org.deeplearning4j.spark.models.embeddings.glove
-
Convert string to vocab words
- VocabWordPairs(Broadcast<VocabCache<VocabWord>>) - Constructor for class org.deeplearning4j.spark.models.embeddings.glove.VocabWordPairs
-
- vocabWords() - Method in class org.deeplearning4j.models.word2vec.wordstore.inmemory.AbstractCache
-
Returns collection of SequenceElements stored in this vocabulary
- vocabWords() - Method in class org.deeplearning4j.models.word2vec.wordstore.inmemory.InMemoryLookupCache
-
Deprecated.
Returns all of the vocab word nodes
- vocabWords() - Method in interface org.deeplearning4j.models.word2vec.wordstore.VocabCache
-
Returns all of the vocab word nodes
- VocabWork - Class in org.deeplearning4j.models.word2vec
-
Vocab work meant for use with the vocab actor
- VocabWork(AtomicInteger, String, boolean) - Constructor for class org.deeplearning4j.models.word2vec.VocabWork
-
- VocabWork(AtomicInteger, String, boolean, String) - Constructor for class org.deeplearning4j.models.word2vec.VocabWork
-
- VocabWork(AtomicInteger, String, boolean, List<String>) - Constructor for class org.deeplearning4j.models.word2vec.VocabWork
-
- VOCLabels - Class in org.deeplearning4j.zoo.util.darknet
-
Helper class that returns label descriptions for YOLO models trained with Pascal VOC.
- VOCLabels() - Constructor for class org.deeplearning4j.zoo.util.darknet.VOCLabels
-
- voidConfiguration - Variable in class org.deeplearning4j.spark.parameterserver.conf.SharedTrainingConfiguration
-
- voidConfiguration - Variable in class org.deeplearning4j.spark.parameterserver.networking.SilentTrainingDriver
-
- voidConfiguration - Variable in class org.deeplearning4j.spark.parameterserver.training.SharedTrainingMaster.Builder
-
- voidConfiguration - Variable in class org.deeplearning4j.spark.parameterserver.training.SharedTrainingMaster
-
- voidConfigurationBroadcast - Variable in class org.deeplearning4j.spark.models.sequencevectors.functions.CountFunction
-
- VoidVertexFactory - Class in org.deeplearning4j.graph.vertexfactory
-
- VoidVertexFactory() - Constructor for class org.deeplearning4j.graph.vertexfactory.VoidVertexFactory
-
- VPTree - Class in org.deeplearning4j.clustering.vptree
-
Vantage point tree implementation
- VPTree(INDArray, boolean) - Constructor for class org.deeplearning4j.clustering.vptree.VPTree
-
- VPTree(INDArray, boolean, int) - Constructor for class org.deeplearning4j.clustering.vptree.VPTree
-
- VPTree(INDArray, String, boolean) - Constructor for class org.deeplearning4j.clustering.vptree.VPTree
-
- VPTree(List<DataPoint>, String, int, boolean) - Constructor for class org.deeplearning4j.clustering.vptree.VPTree
-
- VPTree(INDArray, String) - Constructor for class org.deeplearning4j.clustering.vptree.VPTree
-
- VPTree(INDArray, String, int, boolean) - Constructor for class org.deeplearning4j.clustering.vptree.VPTree
-
- VPTree(List<DataPoint>, String) - Constructor for class org.deeplearning4j.clustering.vptree.VPTree
-
- VPTree(INDArray) - Constructor for class org.deeplearning4j.clustering.vptree.VPTree
-
- VPTree(List<DataPoint>) - Constructor for class org.deeplearning4j.clustering.vptree.VPTree
-
- vpTree - Variable in class org.deeplearning4j.models.embeddings.reader.impl.TreeModelUtils
-
- VPTree.HeapObjectComparator - Class in org.deeplearning4j.clustering.vptree
-
- VPTree.Node - Class in org.deeplearning4j.clustering.vptree
-
- VPTree.NodeBuilder - Class in org.deeplearning4j.clustering.vptree
-
- VPTreeFillSearch - Class in org.deeplearning4j.clustering.vptree
-
Brute force search
for running search
relative to a target
but forced to fill the result list
until the desired k is matched.
- VPTreeFillSearch(VPTree, int, INDArray) - Constructor for class org.deeplearning4j.clustering.vptree.VPTreeFillSearch
-
- vpTreeWorkers(int) - Method in class org.deeplearning4j.plot.BarnesHutTsne.Builder
-
- w_0(double[], double[], int) - Static method in class org.deeplearning4j.clustering.util.MathUtils
-
- w_1(double[], double[], int) - Static method in class org.deeplearning4j.clustering.util.MathUtils
-
- W_KEY - Static variable in class org.deeplearning4j.nn.layers.ocnn.OCNNParamInitializer
-
- waitTillDone() - Method in class org.deeplearning4j.parallelism.inference.observers.BasicInferenceObserver
-
FOR DEBUGGING ONLY, TO BE REMOVED BEFORE MERGE
- waitTillDone() - Method in class org.deeplearning4j.spark.parameterserver.util.BlockingObserver
-
This method blocks until state is set to True
- waitTillRunning() - Method in class org.deeplearning4j.parallelism.trainer.DefaultTrainer
-
- waitTillRunning() - Method in interface org.deeplearning4j.parallelism.trainer.Trainer
-
Block the main thread
till the trainer is up and running.
- walk() - Method in class org.ansj.recognition.impl.NatureRecognition
-
- walk(Vertex<V>, int) - Method in class org.deeplearning4j.models.sequencevectors.graph.walkers.impl.NearestVertexWalker
-
- WalkDirection - Enum in org.deeplearning4j.models.sequencevectors.graph.enums
-
This enum describes walker behavior when choosing next hop.
- walkDirection - Variable in class org.deeplearning4j.models.sequencevectors.graph.walkers.impl.RandomWalker.Builder
-
- walkDirection - Variable in class org.deeplearning4j.models.sequencevectors.graph.walkers.impl.RandomWalker
-
- walker - Variable in class org.deeplearning4j.models.sequencevectors.transformers.impl.GraphTransformer.Builder
-
- walker - Variable in class org.deeplearning4j.models.sequencevectors.transformers.impl.GraphTransformer
-
- walkLength() - Method in interface org.deeplearning4j.graph.iterator.GraphWalkIterator
-
Length of the walks returned by next()
Note that a walk of length i contains i+1 vertices
- walkLength() - Method in class org.deeplearning4j.graph.iterator.RandomWalkIterator
-
- walkLength() - Method in class org.deeplearning4j.graph.iterator.WeightedRandomWalkIterator
-
- walkLength - Variable in class org.deeplearning4j.models.sequencevectors.graph.walkers.impl.NearestVertexWalker.Builder
-
- walkLength - Variable in class org.deeplearning4j.models.sequencevectors.graph.walkers.impl.NearestVertexWalker
-
- walkLength - Variable in class org.deeplearning4j.models.sequencevectors.graph.walkers.impl.RandomWalker.Builder
-
- walkLength - Variable in class org.deeplearning4j.models.sequencevectors.graph.walkers.impl.RandomWalker
-
- WalkMode - Enum in org.deeplearning4j.models.sequencevectors.graph.enums
-
- walkPath() - Method in class org.ansj.util.Graph
-
- walkPath(Map<String, Double>) - Method in class org.ansj.util.Graph
-
干涉性增加相对权重
- walkPathByScore() - Method in class org.ansj.util.Graph
-
- WapitiCRFModel - Class in org.ansj.app.crf.model
-
加载wapiti生成的crf模型,测试使用的wapiti版本为:Wapiti v1.5.0
wapiti 下载地址:https://wapiti.limsi.fr/#download 在这里感谢作者所做的工作.
- WapitiCRFModel() - Constructor for class org.ansj.app.crf.model.WapitiCRFModel
-
- wasAveraged - Variable in class org.deeplearning4j.parallelism.ParallelWrapper
-
- WebReporter - Class in org.deeplearning4j.ui
-
This is simple wrapper for sending state updates generated by `TrainingListener`s.
- WEIGHT_KEY - Static variable in class org.deeplearning4j.nn.params.CenterLossParamInitializer
-
- WEIGHT_KEY - Static variable in class org.deeplearning4j.nn.params.Convolution3DParamInitializer
-
- WEIGHT_KEY - Static variable in class org.deeplearning4j.nn.params.ConvolutionParamInitializer
-
- WEIGHT_KEY - Static variable in class org.deeplearning4j.nn.params.DefaultParamInitializer
-
- WEIGHT_KEY - Static variable in class org.deeplearning4j.nn.params.DepthwiseConvolutionParamInitializer
-
- WEIGHT_KEY - Static variable in class org.deeplearning4j.nn.params.SimpleRnnParamInitializer
-
- WEIGHT_KEY_SUFFIX - Static variable in class org.deeplearning4j.nn.params.VariationalAutoencoderParamInitializer
-
- weightConstraints - Variable in class org.deeplearning4j.nn.conf.layers.Layer.Builder
-
- weightConstraints - Variable in class org.deeplearning4j.nn.conf.NeuralNetConfiguration.Builder
-
- WeightedEdgeLineProcessor - Class in org.deeplearning4j.graph.data.impl
-
A simple line processor, for data in the format 0<delim>1<delim>weight.
- WeightedEdgeLineProcessor(String, boolean) - Constructor for class org.deeplearning4j.graph.data.impl.WeightedEdgeLineProcessor
-
- WeightedEdgeLineProcessor(String, boolean, String...) - Constructor for class org.deeplearning4j.graph.data.impl.WeightedEdgeLineProcessor
-
- WeightedRandomWalkGraphIteratorProvider<V> - Class in org.deeplearning4j.graph.iterator.parallel
-
Weighted random walk graph iterator provider: given a weighted graph (of type IGraph<?,? extends Number>),
split up the generation of weighted random walks for parallel learning.
- WeightedRandomWalkGraphIteratorProvider(IGraph<V, ? extends Number>, int) - Constructor for class org.deeplearning4j.graph.iterator.parallel.WeightedRandomWalkGraphIteratorProvider
-
- WeightedRandomWalkGraphIteratorProvider(IGraph<V, ? extends Number>, int, long, NoEdgeHandling) - Constructor for class org.deeplearning4j.graph.iterator.parallel.WeightedRandomWalkGraphIteratorProvider
-
- WeightedRandomWalkIterator<V> - Class in org.deeplearning4j.graph.iterator
-
Given a graph, iterate through random walks on that graph of a specified length.
- WeightedRandomWalkIterator(IGraph<V, ? extends Number>, int) - Constructor for class org.deeplearning4j.graph.iterator.WeightedRandomWalkIterator
-
- WeightedRandomWalkIterator(IGraph<V, ? extends Number>, int, long) - Constructor for class org.deeplearning4j.graph.iterator.WeightedRandomWalkIterator
-
Construct a RandomWalkIterator for a given graph, with a specified walk length and random number generator seed.
Uses NoEdgeHandling.EXCEPTION_ON_DISCONNECTED - hence exception will be thrown when generating random
walks on graphs with vertices containing having no edges, or no outgoing edges (for directed graphs)
- WeightedRandomWalkIterator(IGraph<V, ? extends Number>, int, long, NoEdgeHandling) - Constructor for class org.deeplearning4j.graph.iterator.WeightedRandomWalkIterator
-
- WeightedRandomWalkIterator(IGraph<V, ? extends Number>, int, long, NoEdgeHandling, int, int) - Constructor for class org.deeplearning4j.graph.iterator.WeightedRandomWalkIterator
-
Constructor used to generate random walks starting at a subset of the vertices in the graph.
- WeightedWalker<T extends SequenceElement> - Class in org.deeplearning4j.models.sequencevectors.graph.walkers.impl
-
This is vertex weight-based walker for SequenceVectors-based DeepWalk implementation.
- WeightedWalker() - Constructor for class org.deeplearning4j.models.sequencevectors.graph.walkers.impl.WeightedWalker
-
- WeightedWalker.Builder<T extends SequenceElement> - Class in org.deeplearning4j.models.sequencevectors.graph.walkers.impl
-
- weightInit - Variable in class org.deeplearning4j.nn.conf.layers.BaseLayer.Builder
-
- weightInit(WeightInit) - Method in class org.deeplearning4j.nn.conf.layers.BaseLayer.Builder
-
Weight initialization scheme to use, for initial weight values
- weightInit(Distribution) - Method in class org.deeplearning4j.nn.conf.layers.BaseLayer.Builder
-
Set weight initialization scheme to random sampling via the specified distribution.
- weightInit - Variable in class org.deeplearning4j.nn.conf.layers.BaseLayer
-
- weightInit - Variable in class org.deeplearning4j.nn.conf.layers.samediff.BaseSameDiffLayer.Builder
-
- weightInit(WeightInit) - Method in class org.deeplearning4j.nn.conf.layers.samediff.BaseSameDiffLayer.Builder
-
- weightInit - Variable in class org.deeplearning4j.nn.conf.layers.samediff.BaseSameDiffLayer
-
- weightInit - Variable in class org.deeplearning4j.nn.conf.NeuralNetConfiguration.Builder
-
- weightInit(WeightInit) - Method in class org.deeplearning4j.nn.conf.NeuralNetConfiguration.Builder
-
Weight initialization scheme.
Note: values set by this method will be applied to all applicable layers in the network, unless a different
value is explicitly set on a given layer.
- weightInit(Distribution) - Method in class org.deeplearning4j.nn.conf.NeuralNetConfiguration.Builder
-
Set weight initialization scheme to random sampling via the specified distribution.
- weightInit(WeightInit) - Method in class org.deeplearning4j.nn.transferlearning.FineTuneConfiguration.Builder
-
Weight initialization scheme
- weightInit(Distribution) - Method in class org.deeplearning4j.nn.transferlearning.FineTuneConfiguration.Builder
-
Set weight initialization scheme to random sampling via the specified distribution.
Equivalent to: .weightInit(WeightInit.DISTRIBUTION).dist(distribution)
- weightInit - Variable in class org.deeplearning4j.nn.transferlearning.FineTuneConfiguration
-
- WeightInit - Enum in org.deeplearning4j.nn.weights
-
Weight initialization scheme
- weightInitRecurrent - Variable in class org.deeplearning4j.nn.conf.layers.BaseRecurrentLayer.Builder
-
- weightInitRecurrent(WeightInit) - Method in class org.deeplearning4j.nn.conf.layers.BaseRecurrentLayer.Builder
-
Set the weight initialization for the recurrent weights.
- weightInitRecurrent(Distribution) - Method in class org.deeplearning4j.nn.conf.layers.BaseRecurrentLayer.Builder
-
Set the weight initialization for the recurrent weights, based on the specified distribution.
- weightInitRecurrent - Variable in class org.deeplearning4j.nn.conf.layers.BaseRecurrentLayer
-
- WeightInitUtil - Class in org.deeplearning4j.nn.weights
-
Weight initialization utility
- WeightIterator() - Constructor for class org.deeplearning4j.models.embeddings.inmemory.InMemoryLookupTable.WeightIterator
-
- weightKeys(Layer) - Method in interface org.deeplearning4j.nn.api.ParamInitializer
-
Weight parameter keys given the layer configuration
- weightKeys(Layer) - Method in class org.deeplearning4j.nn.layers.ocnn.OCNNParamInitializer
-
- weightKeys(Layer) - Method in class org.deeplearning4j.nn.params.BatchNormalizationParamInitializer
-
- weightKeys(Layer) - Method in class org.deeplearning4j.nn.params.BidirectionalParamInitializer
-
- weightKeys(Layer) - Method in class org.deeplearning4j.nn.params.ConvolutionParamInitializer
-
- weightKeys(Layer) - Method in class org.deeplearning4j.nn.params.DefaultParamInitializer
-
- weightKeys(Layer) - Method in class org.deeplearning4j.nn.params.DepthwiseConvolutionParamInitializer
-
- weightKeys(Layer) - Method in class org.deeplearning4j.nn.params.EmptyParamInitializer
-
- weightKeys(Layer) - Method in class org.deeplearning4j.nn.params.FrozenLayerParamInitializer
-
- weightKeys(Layer) - Method in class org.deeplearning4j.nn.params.FrozenLayerWithBackpropParamInitializer
-
- weightKeys(Layer) - Method in class org.deeplearning4j.nn.params.GravesBidirectionalLSTMParamInitializer
-
- weightKeys(Layer) - Method in class org.deeplearning4j.nn.params.GravesLSTMParamInitializer
-
- weightKeys(Layer) - Method in class org.deeplearning4j.nn.params.LSTMParamInitializer
-
- weightKeys(Layer) - Method in class org.deeplearning4j.nn.params.SameDiffParamInitializer
-
- weightKeys(Layer) - Method in class org.deeplearning4j.nn.params.SeparableConvolutionParamInitializer
-
- weightKeys(Layer) - Method in class org.deeplearning4j.nn.params.SimpleRnnParamInitializer
-
- weightKeys(Layer) - Method in class org.deeplearning4j.nn.params.VariationalAutoencoderParamInitializer
-
- weightKeys(Layer) - Method in class org.deeplearning4j.nn.params.WrapperLayerParamInitializer
-
- weightL1Regularization - Variable in class org.deeplearning4j.nn.modelimport.keras.KerasLayer
-
- weightL2Regularization - Variable in class org.deeplearning4j.nn.modelimport.keras.KerasLayer
-
- WeightLookupTable<T extends SequenceElement> - Interface in org.deeplearning4j.models.embeddings
-
General weight lookup table
- weightNoise - Variable in class org.deeplearning4j.nn.conf.layers.BaseLayer.Builder
-
- weightNoise(IWeightNoise) - Method in class org.deeplearning4j.nn.conf.layers.BaseLayer.Builder
-
- weightNoise - Variable in class org.deeplearning4j.nn.conf.layers.BaseLayer
-
- weightNoise - Variable in class org.deeplearning4j.nn.conf.NeuralNetConfiguration.Builder
-
- weightNoise(IWeightNoise) - Method in class org.deeplearning4j.nn.conf.NeuralNetConfiguration.Builder
-
Set the weight noise (such as
DropConnect and
WeightNoise) for the layers in this network.
Note: values set by this method will be applied to all applicable layers in the network, unless a different
value is explicitly set on a given layer.
- WeightNoise - Class in org.deeplearning4j.nn.conf.weightnoise
-
Apply noise of the specified distribution to the weights at training time.
- WeightNoise(Distribution) - Constructor for class org.deeplearning4j.nn.conf.weightnoise.WeightNoise
-
- WeightNoise(Distribution, boolean) - Constructor for class org.deeplearning4j.nn.conf.weightnoise.WeightNoise
-
- WeightNoise(Distribution, boolean, boolean) - Constructor for class org.deeplearning4j.nn.conf.weightnoise.WeightNoise
-
- weightNoise(IWeightNoise) - Method in class org.deeplearning4j.nn.transferlearning.FineTuneConfiguration.Builder
-
- weightNoise - Variable in class org.deeplearning4j.nn.transferlearning.FineTuneConfiguration
-
- weightNoiseParams - Variable in class org.deeplearning4j.nn.layers.BaseLayer
-
- weightNoiseParams - Variable in class org.deeplearning4j.nn.layers.variational.VariationalAutoencoder
-
- weights - Variable in class org.deeplearning4j.nn.modelimport.keras.KerasLayer
-
- weights(InMemoryLookupTable) - Method in class org.deeplearning4j.spark.models.embeddings.word2vec.Word2VecParam.Builder
-
Deprecated.
- weightsArchive - Variable in class org.deeplearning4j.nn.modelimport.keras.utils.KerasModelBuilder
-
- weightsFor(List<Double>) - Static method in class org.deeplearning4j.clustering.util.MathUtils
-
This returns the minimized loss values for a given vector.
- weightsFor(double[]) - Static method in class org.deeplearning4j.clustering.util.MathUtils
-
This returns the minimized loss values for a given vector.
- weightsHdf5Filename(String) - Method in class org.deeplearning4j.nn.modelimport.keras.utils.KerasModelBuilder
-
- weightsHdf5FilenameNoRoot(String) - Method in class org.deeplearning4j.nn.modelimport.keras.utils.KerasModelBuilder
-
- weightsRoot - Variable in class org.deeplearning4j.nn.modelimport.keras.utils.KerasModelBuilder
-
- whitespaceMode(String) - Method in class org.deeplearning4j.ui.components.table.style.StyleTable.Builder
-
Set the whitespace mode (CSS style tag).
- whitespacePre(boolean) - Method in class org.deeplearning4j.ui.components.text.style.StyleText.Builder
-
If set to true: add a "white-space: pre" to the style.
- width(int) - Method in class org.deeplearning4j.clustering.sptree.Cell
-
- width() - Method in class org.deeplearning4j.clustering.sptree.Cell
-
- WIDTH - Static variable in class org.deeplearning4j.datasets.iterator.impl.CifarDataSetIterator
-
- width - Variable in class org.deeplearning4j.ui.api.Style.Builder
-
- width(double, LengthUnit) - Method in class org.deeplearning4j.ui.api.Style.Builder
-
- widthUnit - Variable in class org.deeplearning4j.ui.api.Style.Builder
-
- window - Variable in class org.deeplearning4j.models.embeddings.learning.impl.elements.CBOW
-
- window - Variable in class org.deeplearning4j.models.embeddings.learning.impl.elements.SkipGram
-
- window - Variable in class org.deeplearning4j.models.embeddings.learning.impl.sequence.DBOW
-
- window - Variable in class org.deeplearning4j.models.embeddings.learning.impl.sequence.DM
-
- window - Variable in class org.deeplearning4j.models.embeddings.wordvectors.WordVectorsImpl
-
- window - Variable in class org.deeplearning4j.models.sequencevectors.SequenceVectors.Builder
-
- window(int) - Method in class org.deeplearning4j.spark.models.embeddings.word2vec.Word2VecParam.Builder
-
Deprecated.
- WINDOW - Static variable in class org.deeplearning4j.spark.models.embeddings.word2vec.Word2VecPerformerVoid
-
Deprecated.
- WINDOW - Static variable in class org.deeplearning4j.spark.models.embeddings.word2vec.Word2VecVariables
-
Deprecated.
- Window - Class in org.deeplearning4j.text.movingwindow
-
A representation of a sliding window.
- Window(Collection<String>, int, int) - Constructor for class org.deeplearning4j.text.movingwindow.Window
-
Creates a window with a context of size 3
- Window(Collection<String>, int, int, int) - Constructor for class org.deeplearning4j.text.movingwindow.Window
-
Initialize a window with the given size
- WindowConverter - Class in org.deeplearning4j.text.movingwindow
-
Util methods for converting windows to
training examples
- windowForWordInPosition(int, int, List<String>) - Static method in class org.deeplearning4j.text.movingwindow.Windows
-
Creates a sliding window from text
- Windows - Class in org.deeplearning4j.text.movingwindow
-
Static utility class for textual based windowing cooccurrences
- windows(InputStream, int) - Static method in class org.deeplearning4j.text.movingwindow.Windows
-
Constructs a list of window of size windowSize.
- windows(InputStream, TokenizerFactory, int) - Static method in class org.deeplearning4j.text.movingwindow.Windows
-
Constructs a list of window of size windowSize.
- windows(String, int) - Static method in class org.deeplearning4j.text.movingwindow.Windows
-
Constructs a list of window of size windowSize.
- windows(String, TokenizerFactory, int, WordVectors) - Static method in class org.deeplearning4j.text.movingwindow.Windows
-
Constructs a list of window of size windowSize.
- windows(String) - Static method in class org.deeplearning4j.text.movingwindow.Windows
-
Constructs a list of window of size windowSize.
- windows(String, TokenizerFactory) - Static method in class org.deeplearning4j.text.movingwindow.Windows
-
Constructs a list of window of size windowSize.
- windows(List<String>, int) - Static method in class org.deeplearning4j.text.movingwindow.Windows
-
Constructs a list of window of size windowSize
- windows() - Method in class org.deeplearning4j.util.MovingWindowMatrix
-
Returns a list of non flattened moving window matrices
- windows(boolean) - Method in class org.deeplearning4j.util.MovingWindowMatrix
-
Moving window, capture a row x column moving window of
a given matrix
- windowSize(int) - Method in class org.deeplearning4j.graph.models.deepwalk.DeepWalk.Builder
-
Sets the window size used in skipgram model
- windowSize - Variable in class org.deeplearning4j.models.glove.AbstractCoOccurrences.Builder
-
- windowSize(int) - Method in class org.deeplearning4j.models.glove.AbstractCoOccurrences.Builder
-
- windowSize - Variable in class org.deeplearning4j.models.glove.AbstractCoOccurrences
-
- windowSize(int) - Method in class org.deeplearning4j.models.glove.Glove.Builder
-
- windowSize(int) - Method in class org.deeplearning4j.models.node2vec.Node2Vec.Builder
-
Deprecated.
- windowSize(int) - Method in class org.deeplearning4j.models.paragraphvectors.ParagraphVectors.Builder
-
This method defines context window size
- windowSize(int) - Method in class org.deeplearning4j.models.sequencevectors.SequenceVectors.Builder
-
Sets window size for skip-Gram training
- windowSize(int) - Method in class org.deeplearning4j.models.word2vec.Word2Vec.Builder
-
This method defines context window size
- windowSize - Variable in class org.deeplearning4j.spark.models.embeddings.word2vec.Word2Vec.Builder
-
- windowSize(int) - Method in class org.deeplearning4j.spark.models.embeddings.word2vec.Word2Vec.Builder
-
Specifies window size
- WiredEncodingHandler - Class in org.deeplearning4j.spark.parameterserver.networking
-
This MessageHandler implementation does the same as EncodingHandler, plus additionally:
sends encoded messages over the wire + receives encoded messages from outer parties
- WiredEncodingHandler() - Constructor for class org.deeplearning4j.spark.parameterserver.networking.WiredEncodingHandler
-
This method builds new WiredEncodingHandler instance with initial encoding of 1e-3
- WiredEncodingHandler(double) - Constructor for class org.deeplearning4j.spark.parameterserver.networking.WiredEncodingHandler
-
This method builds new WiredEncodingHandler instance
- WiredEncodingHandler(double, Double) - Constructor for class org.deeplearning4j.spark.parameterserver.networking.WiredEncodingHandler
-
This method builds new WiredEncodingHandler instance
- WiredEncodingHandler(double, double, double, double, int, int) - Constructor for class org.deeplearning4j.spark.parameterserver.networking.WiredEncodingHandler
-
This method builds new WiredEncodingHandler instance
- WiredEncodingHandler(double, double, double, double, int, int, Double) - Constructor for class org.deeplearning4j.spark.parameterserver.networking.WiredEncodingHandler
-
This method builds new WiredEncodingHandler instance
- with(K, V) - Static method in class org.ansj.domain.KV
-
- with(ArrayType, String, WorkspaceConfiguration) - Method in class org.deeplearning4j.nn.workspace.LayerWorkspaceMgr.Builder
-
Configure the workspace (name, configuration) for the specified array type
- Word2Vec - Class in org.deeplearning4j.models.word2vec
-
This is Word2Vec implementation based on SequenceVectors
- Word2Vec() - Constructor for class org.deeplearning4j.models.word2vec.Word2Vec
-
- Word2Vec - Class in org.deeplearning4j.spark.models.embeddings.word2vec
-
Spark version of word2vec
- Word2Vec(INDArray) - Constructor for class org.deeplearning4j.spark.models.embeddings.word2vec.Word2Vec
-
- Word2Vec() - Constructor for class org.deeplearning4j.spark.models.embeddings.word2vec.Word2Vec
-
- word2Vec - Variable in class org.deeplearning4j.spark.models.sequencevectors.export.impl.VocabCacheExporter
-
- Word2Vec.Builder - Class in org.deeplearning4j.models.word2vec
-
- Word2Vec.Builder - Class in org.deeplearning4j.spark.models.embeddings.word2vec
-
- Word2VecChange - Class in org.deeplearning4j.spark.models.embeddings.word2vec
-
Deprecated.
- Word2VecChange(List<Triple<Integer, Integer, Integer>>, Word2VecParam) - Constructor for class org.deeplearning4j.spark.models.embeddings.word2vec.Word2VecChange
-
Deprecated.
- Word2VecDataFetcher - Class in org.deeplearning4j.models.word2vec.iterator
-
- Word2VecDataFetcher(String, Word2Vec, List<String>) - Constructor for class org.deeplearning4j.models.word2vec.iterator.Word2VecDataFetcher
-
- Word2VecDataSetIterator - Class in org.deeplearning4j.models.word2vec.iterator
-
Iterates over a sentence with moving window to produce a data applyTransformToDestination
for word windows based on a pretrained word2vec.
- Word2VecDataSetIterator(Word2Vec, LabelAwareSentenceIterator, List<String>, int, boolean, boolean) - Constructor for class org.deeplearning4j.models.word2vec.iterator.Word2VecDataSetIterator
-
Allows for customization of all of the params of the iterator
- Word2VecDataSetIterator(Word2Vec, LabelAwareSentenceIterator, List<String>) - Constructor for class org.deeplearning4j.models.word2vec.iterator.Word2VecDataSetIterator
-
Initializes this iterator with homogenization and adding labels
and a batch size of 10
- Word2VecDataSetIterator(Word2Vec, LabelAwareSentenceIterator, List<String>, int) - Constructor for class org.deeplearning4j.models.word2vec.iterator.Word2VecDataSetIterator
-
Initializes this iterator with homogenization and adding labels
- Word2VecFuncCall - Class in org.deeplearning4j.spark.models.embeddings.word2vec
-
Deprecated.
- Word2VecFuncCall(Broadcast<Word2VecParam>, Long, List<VocabWord>) - Constructor for class org.deeplearning4j.spark.models.embeddings.word2vec.Word2VecFuncCall
-
Deprecated.
- Word2VecParam - Class in org.deeplearning4j.spark.models.embeddings.word2vec
-
Deprecated.
- Word2VecParam(boolean, double, int, INDArray, int, AtomicLong, double, double, int, int, Broadcast<AtomicLong>, InMemoryLookupTable, int, Broadcast<double[]>) - Constructor for class org.deeplearning4j.spark.models.embeddings.word2vec.Word2VecParam
-
Deprecated.
- Word2VecParam.Builder - Class in org.deeplearning4j.spark.models.embeddings.word2vec
-
Deprecated.
- Word2VecPerformer - Class in org.deeplearning4j.spark.models.embeddings.word2vec
-
Deprecated.
- Word2VecPerformer(SparkConf, Broadcast<AtomicLong>, InMemoryLookupTable) - Constructor for class org.deeplearning4j.spark.models.embeddings.word2vec.Word2VecPerformer
-
Deprecated.
- Word2VecPerformerVoid - Class in org.deeplearning4j.spark.models.embeddings.word2vec
-
Deprecated.
- Word2VecPerformerVoid(SparkConf, Broadcast<AtomicLong>, InMemoryLookupTable) - Constructor for class org.deeplearning4j.spark.models.embeddings.word2vec.Word2VecPerformerVoid
-
Deprecated.
- Word2VecSetup - Class in org.deeplearning4j.spark.models.embeddings.word2vec
-
Deprecated.
- Word2VecSetup(Broadcast<Word2VecParam>) - Constructor for class org.deeplearning4j.spark.models.embeddings.word2vec.Word2VecSetup
-
Deprecated.
- Word2VecVariables - Class in org.deeplearning4j.spark.models.embeddings.word2vec
-
Deprecated.
- WORD_COST - Static variable in class com.atilika.kuromoji.dict.DictionaryField
-
- wordAlert(String) - Static method in class org.ansj.app.crf.Config
-
词语标准化
- wordAtIndex(int) - Method in class org.deeplearning4j.models.word2vec.wordstore.inmemory.AbstractCache
-
Returns the label of the element at specified Huffman index
- wordAtIndex(int) - Method in class org.deeplearning4j.models.word2vec.wordstore.inmemory.InMemoryLookupCache
-
Deprecated.
Returns the word contained at the given index or null
- wordAtIndex(int) - Method in interface org.deeplearning4j.models.word2vec.wordstore.VocabCache
-
Returns the word contained at the given index or null
- WordConverter - Class in org.deeplearning4j.text.movingwindow
-
- WordConverter(List<String>, Word2Vec) - Constructor for class org.deeplearning4j.text.movingwindow.WordConverter
-
- wordCost - Variable in class com.atilika.kuromoji.dict.DictionaryEntryBase
-
- wordCost(short) - Method in class com.atilika.kuromoji.dict.GenericDictionaryEntry.Builder
-
- wordCount(Broadcast<AtomicLong>) - Method in class org.deeplearning4j.spark.models.embeddings.word2vec.Word2VecParam.Builder
-
Deprecated.
- wordFor(String) - Method in class org.deeplearning4j.models.word2vec.wordstore.inmemory.AbstractCache
-
Returns SequenceElement for specified label
- wordFor(long) - Method in class org.deeplearning4j.models.word2vec.wordstore.inmemory.AbstractCache
-
- wordFor(String) - Method in class org.deeplearning4j.models.word2vec.wordstore.inmemory.InMemoryLookupCache
-
Deprecated.
- wordFor(long) - Method in class org.deeplearning4j.models.word2vec.wordstore.inmemory.InMemoryLookupCache
-
Deprecated.
- wordFor(String) - Method in interface org.deeplearning4j.models.word2vec.wordstore.VocabCache
-
- wordFor(long) - Method in interface org.deeplearning4j.models.word2vec.wordstore.VocabCache
-
- WordFreqAccumulator - Class in org.deeplearning4j.spark.text.accumulators
-
- WordFreqAccumulator() - Constructor for class org.deeplearning4j.spark.text.accumulators.WordFreqAccumulator
-
- wordFrequencies - Variable in class org.deeplearning4j.models.word2vec.wordstore.inmemory.InMemoryLookupCache
-
Deprecated.
- wordFrequency(String) - Method in class org.deeplearning4j.models.word2vec.wordstore.inmemory.AbstractCache
-
Returns the SequenceElement's frequency over training corpus
- wordFrequency(String) - Method in class org.deeplearning4j.models.word2vec.wordstore.inmemory.InMemoryLookupCache
-
Deprecated.
Returns the number of times the word has occurred
- wordFrequency(String) - Method in interface org.deeplearning4j.models.word2vec.wordstore.VocabCache
-
Returns the number of times the word has occurred
- WordIdMap - Class in com.atilika.kuromoji.buffer
-
- WordIdMap(InputStream) - Constructor for class com.atilika.kuromoji.buffer.WordIdMap
-
- wordIdMap - Variable in class com.atilika.kuromoji.dict.TokenInfoDictionary
-
- WordIdMapCompiler - Class in com.atilika.kuromoji.compile
-
- WordIdMapCompiler() - Constructor for class com.atilika.kuromoji.compile.WordIdMapCompiler
-
- WordIdMapCompiler.GrowableIntArray - Class in com.atilika.kuromoji.compile
-
- wordIdsCompiler - Variable in class com.atilika.kuromoji.compile.TokenInfoDictionaryCompilerBase
-
- words() - Method in class org.deeplearning4j.models.word2vec.wordstore.inmemory.AbstractCache
-
Returns collection of labels available in this vocabulary
- words() - Method in class org.deeplearning4j.models.word2vec.wordstore.inmemory.InMemoryLookupCache
-
Deprecated.
Returns all of the words in the vocab
- words() - Method in interface org.deeplearning4j.models.word2vec.wordstore.VocabCache
-
Returns all of the words in the vocab
- words() - Method in class org.deeplearning4j.models.word2vec.wordstore.VocabularyHolder
-
Returns sorted list of words in vocabulary.
- WordSimilarity() - Constructor for class org.deeplearning4j.models.embeddings.reader.impl.BasicModelUtils.WordSimilarity
-
- WordsListToVocabWordsFunction - Class in org.deeplearning4j.spark.text.functions
-
- WordsListToVocabWordsFunction(Broadcast<VocabCache<VocabWord>>) - Constructor for class org.deeplearning4j.spark.text.functions.WordsListToVocabWordsFunction
-
- wordsNearest(String, int) - Method in class org.deeplearning4j.models.embeddings.reader.impl.BasicModelUtils
-
- wordsNearest(Collection<String>, Collection<String>, int) - Method in class org.deeplearning4j.models.embeddings.reader.impl.BasicModelUtils
-
- wordsNearest(INDArray, int) - Method in class org.deeplearning4j.models.embeddings.reader.impl.BasicModelUtils
-
Words nearest based on positive and negative words
* @param top the top n words
- wordsNearest(String, int) - Method in class org.deeplearning4j.models.embeddings.reader.impl.FlatModelUtils
-
This method does full scan against whole vocabulary, building descending list of similar words
- wordsNearest(INDArray, int) - Method in class org.deeplearning4j.models.embeddings.reader.impl.FlatModelUtils
-
This method does full scan against whole vocabulary, building descending list of similar words
- wordsNearest(String, int) - Method in class org.deeplearning4j.models.embeddings.reader.impl.TreeModelUtils
-
This method returns nearest words for target word, based on tree structure.
- wordsNearest(Collection<String>, Collection<String>, int) - Method in class org.deeplearning4j.models.embeddings.reader.impl.TreeModelUtils
-
- wordsNearest(INDArray, int) - Method in class org.deeplearning4j.models.embeddings.reader.impl.TreeModelUtils
-
- wordsNearest(String, int) - Method in interface org.deeplearning4j.models.embeddings.reader.ModelUtils
-
This method implementations should return N nearest elements labels to given element's label
- wordsNearest(Collection<String>, Collection<String>, int) - Method in interface org.deeplearning4j.models.embeddings.reader.ModelUtils
-
Words nearest based on positive and negative words
- wordsNearest(INDArray, int) - Method in interface org.deeplearning4j.models.embeddings.reader.ModelUtils
-
Words nearest based on positive and negative words
* @param top the top n words
- wordsNearest(INDArray, int) - Method in interface org.deeplearning4j.models.embeddings.wordvectors.WordVectors
-
- wordsNearest(Collection<String>, Collection<String>, int) - Method in interface org.deeplearning4j.models.embeddings.wordvectors.WordVectors
-
Words nearest based on positive and negative words
- wordsNearest(String, int) - Method in interface org.deeplearning4j.models.embeddings.wordvectors.WordVectors
-
Get the top n words most similar to the given word
- wordsNearest(INDArray, int) - Method in class org.deeplearning4j.models.embeddings.wordvectors.WordVectorsImpl
-
Words nearest based on positive and negative words
* @param top the top n words
- wordsNearest(Collection<String>, Collection<String>, int) - Method in class org.deeplearning4j.models.embeddings.wordvectors.WordVectorsImpl
-
Words nearest based on positive and negative words
- wordsNearest(String, int) - Method in class org.deeplearning4j.models.embeddings.wordvectors.WordVectorsImpl
-
Get the top n words most similar to the given word
- wordsNearest(INDArray, int) - Method in class org.deeplearning4j.models.word2vec.StaticWord2Vec
-
- wordsNearest(Collection<String>, Collection<String>, int) - Method in class org.deeplearning4j.models.word2vec.StaticWord2Vec
-
Words nearest based on positive and negative words
PLEASE NOTE: This method is not available in this implementation.
- wordsNearest(String, int) - Method in class org.deeplearning4j.models.word2vec.StaticWord2Vec
-
Get the top n words most similar to the given word
PLEASE NOTE: This method is not available in this implementation.
- wordsNearestSum(String, int) - Method in class org.deeplearning4j.models.embeddings.reader.impl.BasicModelUtils
-
Get the top n words most similar to the given word
- wordsNearestSum(INDArray, int) - Method in class org.deeplearning4j.models.embeddings.reader.impl.BasicModelUtils
-
Words nearest based on positive and negative words
* @param top the top n words
- wordsNearestSum(Collection<String>, Collection<String>, int) - Method in class org.deeplearning4j.models.embeddings.reader.impl.BasicModelUtils
-
Words nearest based on positive and negative words
- wordsNearestSum(String, int) - Method in interface org.deeplearning4j.models.embeddings.reader.ModelUtils
-
- wordsNearestSum(INDArray, int) - Method in interface org.deeplearning4j.models.embeddings.reader.ModelUtils
-
- wordsNearestSum(Collection<String>, Collection<String>, int) - Method in interface org.deeplearning4j.models.embeddings.reader.ModelUtils
-
- wordsNearestSum(INDArray, int) - Method in interface org.deeplearning4j.models.embeddings.wordvectors.WordVectors
-
- wordsNearestSum(String, int) - Method in interface org.deeplearning4j.models.embeddings.wordvectors.WordVectors
-
Get the top n words most similar to the given word
- wordsNearestSum(Collection<String>, Collection<String>, int) - Method in interface org.deeplearning4j.models.embeddings.wordvectors.WordVectors
-
Words nearest based on positive and negative words
- wordsNearestSum(Collection<String>, Collection<String>, int) - Method in class org.deeplearning4j.models.embeddings.wordvectors.WordVectorsImpl
-
Words nearest based on positive and negative words
- wordsNearestSum(INDArray, int) - Method in class org.deeplearning4j.models.embeddings.wordvectors.WordVectorsImpl
-
Words nearest based on positive and negative words
* @param top the top n words
- wordsNearestSum(String, int) - Method in class org.deeplearning4j.models.embeddings.wordvectors.WordVectorsImpl
-
Get the top n words most similar to the given word
- wordsNearestSum(INDArray, int) - Method in class org.deeplearning4j.models.word2vec.StaticWord2Vec
-
- wordsNearestSum(String, int) - Method in class org.deeplearning4j.models.word2vec.StaticWord2Vec
-
Get the top n words most similar to the given word
PLEASE NOTE: This method is not available in this implementation.
- wordsNearestSum(Collection<String>, Collection<String>, int) - Method in class org.deeplearning4j.models.word2vec.StaticWord2Vec
-
Words nearest based on positive and negative words
PLEASE NOTE: This method is not available in this implementation.
- wordVectors(WordVectors) - Method in class org.deeplearning4j.iterator.CnnSentenceDataSetIterator.Builder
-
Provide the WordVectors instance that should be used for training
- WordVectors - Interface in org.deeplearning4j.models.embeddings.wordvectors
-
Word vectors.
- WordVectorSerializer - Class in org.deeplearning4j.models.embeddings.loader
-
This is utility class, providing various methods for WordVectors serialization
- WordVectorSerializer.BinaryReader - Class in org.deeplearning4j.models.embeddings.loader
-
- WordVectorSerializer.CSVReader - Class in org.deeplearning4j.models.embeddings.loader
-
- WordVectorSerializer.Reader - Interface in org.deeplearning4j.models.embeddings.loader
-
- WordVectorsImpl<T extends SequenceElement> - Class in org.deeplearning4j.models.embeddings.wordvectors
-
Common word vector operations
- WordVectorsImpl() - Constructor for class org.deeplearning4j.models.embeddings.wordvectors.WordVectorsImpl
-
- WORKER_FLAT_MAP_DATA_SET_GET_TIMES_MS - Static variable in class org.deeplearning4j.spark.api.stats.CommonSparkTrainingStats
-
- WORKER_FLAT_MAP_GET_INITIAL_MODEL_TIME_MS - Static variable in class org.deeplearning4j.spark.api.stats.CommonSparkTrainingStats
-
- WORKER_FLAT_MAP_PROCESS_MINI_BATCH_TIMES_MS - Static variable in class org.deeplearning4j.spark.api.stats.CommonSparkTrainingStats
-
- WORKER_FLAT_MAP_TOTAL_TIME_MS - Static variable in class org.deeplearning4j.spark.api.stats.CommonSparkTrainingStats
-
- WorkerConfiguration - Class in org.deeplearning4j.spark.api
-
A simple configuration object (common settings for workers)
- WorkerConfiguration() - Constructor for class org.deeplearning4j.spark.api.WorkerConfiguration
-
- workerCounter - Variable in class org.deeplearning4j.parallelism.ParallelWrapper
-
- workerFlatMapDataSetGetTimesMs(List<EventStats>) - Method in class org.deeplearning4j.spark.api.stats.CommonSparkTrainingStats.Builder
-
- workerFlatMapGetInitialModelTimeMs(List<EventStats>) - Method in class org.deeplearning4j.spark.api.stats.CommonSparkTrainingStats.Builder
-
- workerFlatMapProcessMiniBatchTimesMs(List<EventStats>) - Method in class org.deeplearning4j.spark.api.stats.CommonSparkTrainingStats.Builder
-
- workerFlatMapTotalTimeMs(List<EventStats>) - Method in class org.deeplearning4j.spark.api.stats.CommonSparkTrainingStats.Builder
-
- workerID() - Method in class org.deeplearning4j.ui.stats.sbe.StaticInfoDecoder
-
- workerID(String) - Method in class org.deeplearning4j.ui.stats.sbe.StaticInfoEncoder
-
- workerID() - Method in class org.deeplearning4j.ui.stats.sbe.StorageMetaDataDecoder
-
- workerID(String) - Method in class org.deeplearning4j.ui.stats.sbe.StorageMetaDataEncoder
-
- workerID() - Method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder
-
- workerID(String) - Method in class org.deeplearning4j.ui.stats.sbe.UpdateEncoder
-
- workerIDCharacterEncoding() - Static method in class org.deeplearning4j.ui.stats.sbe.StaticInfoDecoder
-
- workerIDCharacterEncoding() - Static method in class org.deeplearning4j.ui.stats.sbe.StaticInfoEncoder
-
- workerIDCharacterEncoding() - Static method in class org.deeplearning4j.ui.stats.sbe.StorageMetaDataDecoder
-
- workerIDCharacterEncoding() - Static method in class org.deeplearning4j.ui.stats.sbe.StorageMetaDataEncoder
-
- workerIDCharacterEncoding() - Static method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder
-
- workerIDCharacterEncoding() - Static method in class org.deeplearning4j.ui.stats.sbe.UpdateEncoder
-
- workerIDHeaderLength() - Static method in class org.deeplearning4j.ui.stats.sbe.StaticInfoDecoder
-
- workerIDHeaderLength() - Static method in class org.deeplearning4j.ui.stats.sbe.StaticInfoEncoder
-
- workerIDHeaderLength() - Static method in class org.deeplearning4j.ui.stats.sbe.StorageMetaDataDecoder
-
- workerIDHeaderLength() - Static method in class org.deeplearning4j.ui.stats.sbe.StorageMetaDataEncoder
-
- workerIDHeaderLength() - Static method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder
-
- workerIDHeaderLength() - Static method in class org.deeplearning4j.ui.stats.sbe.UpdateEncoder
-
- workerIDId() - Static method in class org.deeplearning4j.ui.stats.sbe.StaticInfoDecoder
-
- workerIDId() - Static method in class org.deeplearning4j.ui.stats.sbe.StaticInfoEncoder
-
- workerIDId() - Static method in class org.deeplearning4j.ui.stats.sbe.StorageMetaDataDecoder
-
- workerIDId() - Static method in class org.deeplearning4j.ui.stats.sbe.StorageMetaDataEncoder
-
- workerIDId() - Static method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder
-
- workerIDId() - Static method in class org.deeplearning4j.ui.stats.sbe.UpdateEncoder
-
- workerIDLength() - Method in class org.deeplearning4j.ui.stats.sbe.StaticInfoDecoder
-
- workerIDLength() - Method in class org.deeplearning4j.ui.stats.sbe.StorageMetaDataDecoder
-
- workerIDLength() - Method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder
-
- workerIDMetaAttribute(MetaAttribute) - Static method in class org.deeplearning4j.ui.stats.sbe.StaticInfoDecoder
-
- workerIDMetaAttribute(MetaAttribute) - Static method in class org.deeplearning4j.ui.stats.sbe.StaticInfoEncoder
-
- workerIDMetaAttribute(MetaAttribute) - Static method in class org.deeplearning4j.ui.stats.sbe.StorageMetaDataDecoder
-
- workerIDMetaAttribute(MetaAttribute) - Static method in class org.deeplearning4j.ui.stats.sbe.StorageMetaDataEncoder
-
- workerIDMetaAttribute(MetaAttribute) - Static method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder
-
- workerIDMetaAttribute(MetaAttribute) - Static method in class org.deeplearning4j.ui.stats.sbe.UpdateEncoder
-
- workerPrefetchNumBatches(int) - Method in class org.deeplearning4j.spark.impl.paramavg.ParameterAveragingTrainingMaster.Builder
-
Set the number of minibatches to asynchronously prefetch in the worker.
- workers - Variable in class org.deeplearning4j.models.embeddings.wordvectors.WordVectorsImpl
-
- workers - Variable in class org.deeplearning4j.models.glove.AbstractCoOccurrences.Builder
-
- workers(int) - Method in class org.deeplearning4j.models.glove.AbstractCoOccurrences.Builder
-
- workers - Variable in class org.deeplearning4j.models.glove.AbstractCoOccurrences
-
- workers(int) - Method in class org.deeplearning4j.models.glove.Glove.Builder
-
- workers(int) - Method in class org.deeplearning4j.models.node2vec.Node2Vec.Builder
-
Deprecated.
- workers(int) - Method in class org.deeplearning4j.models.paragraphvectors.ParagraphVectors.Builder
-
This method defines maximum number of concurrent threads available for training
- workers - Variable in class org.deeplearning4j.models.sequencevectors.SequenceVectors.Builder
-
- workers(int) - Method in class org.deeplearning4j.models.sequencevectors.SequenceVectors.Builder
-
Sets number of worker threads to be used in calculations
- workers(int) - Method in class org.deeplearning4j.models.word2vec.Word2Vec.Builder
-
This method defines maximum number of concurrent threads available for training
- workers(int) - Method in class org.deeplearning4j.parallelism.ParallelInference.Builder
-
This method defines, how many model copies will be used for inference.
- workers - Variable in class org.deeplearning4j.parallelism.ParallelWrapper.Builder
-
- workers(int) - Method in class org.deeplearning4j.parallelism.ParallelWrapper.Builder
-
This method allows to configure number of workers that'll be used for parallel training
- workers - Variable in class org.deeplearning4j.parallelism.ParallelWrapper
-
- workers(int) - Method in class org.deeplearning4j.spark.models.embeddings.word2vec.Word2Vec.Builder
-
Specify number of workers for training process.
- workers - Variable in class org.deeplearning4j.spark.models.sequencevectors.SparkSequenceVectors.Builder
-
- workers(int) - Method in class org.deeplearning4j.spark.models.sequencevectors.SparkSequenceVectors.Builder
-
- workers(int) - Method in class org.deeplearning4j.spark.models.word2vec.SparkWord2Vec.Builder
-
- workersCounter - Variable in class org.deeplearning4j.optimize.solvers.accumulation.EncodedGradientsAccumulator
-
- workersPerNode(int) - Method in class org.deeplearning4j.spark.parameterserver.training.SharedTrainingMaster.Builder
-
This method allows to configure number of trainer threads per cluster node.
- workingMemory(long, long, long, long) - Method in class org.deeplearning4j.nn.conf.memory.LayerMemoryReport.Builder
-
Report the working memory size, for both inference and training
- workingMemory(long, long, Map<CacheMode, Long>, Map<CacheMode, Long>) - Method in class org.deeplearning4j.nn.conf.memory.LayerMemoryReport.Builder
-
Report the working memory requirements, for both inference and training.
- workspace() - Method in class org.deeplearning4j.clustering.sptree.SpTree
-
- workspaceCache - Static variable in class org.deeplearning4j.plot.BarnesHutTsne
-
- workspaceConfigurationCache - Static variable in class org.deeplearning4j.clustering.sptree.SpTree
-
- workspaceConfigurationCache - Static variable in class org.deeplearning4j.plot.BarnesHutTsne
-
- workspaceConfigurationExternal - Static variable in class org.deeplearning4j.clustering.sptree.SpTree
-
- workspaceConfigurationExternal - Static variable in class org.deeplearning4j.plot.BarnesHutTsne
-
- workspaceConfigurationFeedForward - Variable in class org.deeplearning4j.clustering.sptree.SpTree
-
- workspaceConfigurationFeedForward - Variable in class org.deeplearning4j.plot.BarnesHutTsne
-
- workspaceExternal - Static variable in class org.deeplearning4j.clustering.sptree.SpTree
-
- workspaceExternal - Static variable in class org.deeplearning4j.plot.BarnesHutTsne
-
- workspaceId - Variable in class org.deeplearning4j.datasets.iterator.AsyncDataSetIterator
-
- workspaceId - Variable in class org.deeplearning4j.datasets.iterator.AsyncMultiDataSetIterator
-
- workspaceMode - Variable in class org.deeplearning4j.clustering.sptree.SpTree
-
- WorkspaceMode - Enum in org.deeplearning4j.nn.conf
-
Workspace mode to use.
- workspaceMode - Variable in class org.deeplearning4j.parallelism.ParallelWrapper.Builder
-
- workspaceMode(WorkspaceMode) - Method in class org.deeplearning4j.parallelism.ParallelWrapper.Builder
-
- workspaceMode - Variable in class org.deeplearning4j.parallelism.ParallelWrapper
-
- workspaceMode - Variable in class org.deeplearning4j.parallelism.trainer.DefaultTrainer
-
- workspaceMode - Variable in class org.deeplearning4j.plot.BarnesHutTsne
-
- workspaceMode - Variable in class org.deeplearning4j.spark.parameterserver.conf.SharedTrainingConfiguration
-
- workspaces - Variable in class org.deeplearning4j.optimize.solvers.accumulation.EncodedGradientsAccumulator
-
- WorkspacesShieldDataSetIterator - Class in org.deeplearning4j.datasets.iterator
-
This iterator detaches/migrates DataSets coming out from backed DataSetIterator, thus providing "safe" DataSets.
- WorkspacesShieldDataSetIterator(DataSetIterator) - Constructor for class org.deeplearning4j.datasets.iterator.WorkspacesShieldDataSetIterator
-
- wrap(DirectBuffer, int) - Method in class org.deeplearning4j.ui.stats.sbe.GroupSizeEncodingDecoder
-
- wrap(MutableDirectBuffer, int) - Method in class org.deeplearning4j.ui.stats.sbe.GroupSizeEncodingEncoder
-
- wrap(DirectBuffer, int) - Method in class org.deeplearning4j.ui.stats.sbe.InitFieldsPresentDecoder
-
- wrap(MutableDirectBuffer, int) - Method in class org.deeplearning4j.ui.stats.sbe.InitFieldsPresentEncoder
-
- wrap(DirectBuffer, int) - Method in class org.deeplearning4j.ui.stats.sbe.MessageHeaderDecoder
-
- wrap(MutableDirectBuffer, int) - Method in class org.deeplearning4j.ui.stats.sbe.MessageHeaderEncoder
-
- wrap(StaticInfoDecoder, DirectBuffer) - Method in class org.deeplearning4j.ui.stats.sbe.StaticInfoDecoder.HwDeviceInfoGroupDecoder
-
- wrap(StaticInfoDecoder, DirectBuffer) - Method in class org.deeplearning4j.ui.stats.sbe.StaticInfoDecoder.ModelParamNamesDecoder
-
- wrap(StaticInfoDecoder, DirectBuffer) - Method in class org.deeplearning4j.ui.stats.sbe.StaticInfoDecoder.SwEnvironmentInfoDecoder
-
- wrap(DirectBuffer, int, int, int) - Method in class org.deeplearning4j.ui.stats.sbe.StaticInfoDecoder
-
- wrap(StaticInfoEncoder, MutableDirectBuffer, int) - Method in class org.deeplearning4j.ui.stats.sbe.StaticInfoEncoder.HwDeviceInfoGroupEncoder
-
- wrap(StaticInfoEncoder, MutableDirectBuffer, int) - Method in class org.deeplearning4j.ui.stats.sbe.StaticInfoEncoder.ModelParamNamesEncoder
-
- wrap(StaticInfoEncoder, MutableDirectBuffer, int) - Method in class org.deeplearning4j.ui.stats.sbe.StaticInfoEncoder.SwEnvironmentInfoEncoder
-
- wrap(MutableDirectBuffer, int) - Method in class org.deeplearning4j.ui.stats.sbe.StaticInfoEncoder
-
- wrap(StorageMetaDataDecoder, DirectBuffer) - Method in class org.deeplearning4j.ui.stats.sbe.StorageMetaDataDecoder.ExtraMetaDataBytesDecoder
-
- wrap(DirectBuffer, int, int, int) - Method in class org.deeplearning4j.ui.stats.sbe.StorageMetaDataDecoder
-
- wrap(StorageMetaDataEncoder, MutableDirectBuffer, int) - Method in class org.deeplearning4j.ui.stats.sbe.StorageMetaDataEncoder.ExtraMetaDataBytesEncoder
-
- wrap(MutableDirectBuffer, int) - Method in class org.deeplearning4j.ui.stats.sbe.StorageMetaDataEncoder
-
- wrap(UpdateDecoder, DirectBuffer) - Method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder.DataSetMetaDataBytesDecoder.MetaDataBytesDecoder
-
- wrap(UpdateDecoder, DirectBuffer) - Method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder.DataSetMetaDataBytesDecoder
-
- wrap(UpdateDecoder, DirectBuffer) - Method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder.GcStatsDecoder
-
- wrap(UpdateDecoder, DirectBuffer) - Method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder.LayerNamesDecoder
-
- wrap(UpdateDecoder, DirectBuffer) - Method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder.MemoryUseDecoder
-
- wrap(UpdateDecoder, DirectBuffer) - Method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder.ParamNamesDecoder
-
- wrap(UpdateDecoder, DirectBuffer) - Method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder.PerformanceDecoder
-
- wrap(UpdateDecoder, DirectBuffer) - Method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder.PerParameterStatsDecoder.HistogramsDecoder.HistogramCountsDecoder
-
- wrap(UpdateDecoder, DirectBuffer) - Method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder.PerParameterStatsDecoder.HistogramsDecoder
-
- wrap(UpdateDecoder, DirectBuffer) - Method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder.PerParameterStatsDecoder.SummaryStatDecoder
-
- wrap(UpdateDecoder, DirectBuffer) - Method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder.PerParameterStatsDecoder
-
- wrap(DirectBuffer, int, int, int) - Method in class org.deeplearning4j.ui.stats.sbe.UpdateDecoder
-
- wrap(UpdateEncoder, MutableDirectBuffer, int) - Method in class org.deeplearning4j.ui.stats.sbe.UpdateEncoder.DataSetMetaDataBytesEncoder.MetaDataBytesEncoder
-
- wrap(UpdateEncoder, MutableDirectBuffer, int) - Method in class org.deeplearning4j.ui.stats.sbe.UpdateEncoder.DataSetMetaDataBytesEncoder
-
- wrap(UpdateEncoder, MutableDirectBuffer, int) - Method in class org.deeplearning4j.ui.stats.sbe.UpdateEncoder.GcStatsEncoder
-
- wrap(UpdateEncoder, MutableDirectBuffer, int) - Method in class org.deeplearning4j.ui.stats.sbe.UpdateEncoder.LayerNamesEncoder
-
- wrap(UpdateEncoder, MutableDirectBuffer, int) - Method in class org.deeplearning4j.ui.stats.sbe.UpdateEncoder.MemoryUseEncoder
-
- wrap(UpdateEncoder, MutableDirectBuffer, int) - Method in class org.deeplearning4j.ui.stats.sbe.UpdateEncoder.ParamNamesEncoder
-
- wrap(UpdateEncoder, MutableDirectBuffer, int) - Method in class org.deeplearning4j.ui.stats.sbe.UpdateEncoder.PerformanceEncoder
-
- wrap(UpdateEncoder, MutableDirectBuffer, int) - Method in class org.deeplearning4j.ui.stats.sbe.UpdateEncoder.PerParameterStatsEncoder.HistogramsEncoder.HistogramCountsEncoder
-
- wrap(UpdateEncoder, MutableDirectBuffer, int) - Method in class org.deeplearning4j.ui.stats.sbe.UpdateEncoder.PerParameterStatsEncoder.HistogramsEncoder
-
- wrap(UpdateEncoder, MutableDirectBuffer, int) - Method in class org.deeplearning4j.ui.stats.sbe.UpdateEncoder.PerParameterStatsEncoder.SummaryStatEncoder
-
- wrap(UpdateEncoder, MutableDirectBuffer, int) - Method in class org.deeplearning4j.ui.stats.sbe.UpdateEncoder.PerParameterStatsEncoder
-
- wrap(MutableDirectBuffer, int) - Method in class org.deeplearning4j.ui.stats.sbe.UpdateEncoder
-
- wrap(DirectBuffer, int) - Method in class org.deeplearning4j.ui.stats.sbe.UpdateFieldsPresentDecoder
-
- wrap(MutableDirectBuffer, int) - Method in class org.deeplearning4j.ui.stats.sbe.UpdateFieldsPresentEncoder
-
- wrap(DirectBuffer, int) - Method in class org.deeplearning4j.ui.stats.sbe.VarDataUTF8Decoder
-
- wrap(MutableDirectBuffer, int) - Method in class org.deeplearning4j.ui.stats.sbe.VarDataUTF8Encoder
-
- wrapper - Variable in class org.deeplearning4j.spark.parameterserver.pw.SharedTrainingWrapper
-
- WrapperLayerParamInitializer - Class in org.deeplearning4j.nn.params
-
- writableConverter(WritableConverter) - Method in class org.deeplearning4j.datasets.datavec.RecordReaderDataSetIterator.Builder
-
- writableConverter(String) - Method in class org.deeplearning4j.streaming.routes.CamelKafkaRouteBuilder.Builder
-
- write(OutputStream) - Method in class com.atilika.kuromoji.buffer.StringValueMapBuffer
-
- write(String) - Method in class com.atilika.kuromoji.compile.TokenInfoDictionaryCompilerBase
-
- write(OutputStream) - Method in class com.atilika.kuromoji.compile.WordIdMapCompiler
-
- write(OutputStream, ByteBuffer) - Static method in class com.atilika.kuromoji.io.ByteBufferIO
-
- write(OutputStream) - Method in class com.atilika.kuromoji.trie.DoubleArrayTrie
-
- writeArray(OutputStream, int[]) - Static method in class com.atilika.kuromoji.io.IntegerArrayIO
-
- writeArray(OutputStream, String[]) - Static method in class com.atilika.kuromoji.io.StringArrayIO
-
- writeArray2D(OutputStream, int[][]) - Static method in class com.atilika.kuromoji.io.IntegerArrayIO
-
- writeArray2D(OutputStream, String[][]) - Static method in class com.atilika.kuromoji.io.StringArrayIO
-
- writeDictionary(String) - Method in class com.atilika.kuromoji.compile.TokenInfoDictionaryCompilerBase
-
- writeFullModel(Word2Vec, String) - Static method in class org.deeplearning4j.models.embeddings.loader.WordVectorSerializer
-
Deprecated.
- writeGraphVectors(DeepWalk, String) - Static method in class org.deeplearning4j.graph.models.loader.GraphVectorSerializer
-
- writeImageToPpm(int[][], String) - Static method in class org.deeplearning4j.datasets.mnist.MnistManager
-
Writes the given image in the given file using the PPM data format.
- writeMap(String, FeatureInfoMap) - Method in class com.atilika.kuromoji.compile.TokenInfoDictionaryCompilerBase
-
- writeModel(String) - Method in class org.ansj.app.crf.Model
-
将model序列化到硬盘
- writeModel(Model, File, boolean) - Static method in class org.deeplearning4j.util.ModelSerializer
-
Write a model to a file
- writeModel(Model, File, boolean, DataNormalization) - Static method in class org.deeplearning4j.util.ModelSerializer
-
Write a model to a file
- writeModel(Model, String, boolean) - Static method in class org.deeplearning4j.util.ModelSerializer
-
Write a model to a file path
- writeModel(Model, OutputStream, boolean) - Static method in class org.deeplearning4j.util.ModelSerializer
-
Write a model to an output stream
- writeModel(Model, OutputStream, boolean, DataNormalization) - Static method in class org.deeplearning4j.util.ModelSerializer
-
Write a model to an output stream
- writeObject(CoOccurrenceWeight<T>) - Method in class org.deeplearning4j.models.glove.count.ASCIICoOccurrenceWriter
-
- writeObject(CoOccurrenceWeight<T>) - Method in class org.deeplearning4j.models.glove.count.BinaryCoOccurrenceWriter
-
- writeObject(CoOccurrenceWeight<T>) - Method in interface org.deeplearning4j.models.glove.count.CoOccurrenceWriter
-
This method implementations should write out objects immediately
- writeObjectToFile(String, Object, JavaSparkContext) - Static method in class org.deeplearning4j.spark.util.SparkUtils
-
Write an object to HDFS (or local) using default Java object serialization
- writeObjectToFile(String, Object, SparkContext) - Static method in class org.deeplearning4j.spark.util.SparkUtils
-
Write an object to HDFS (or local) using default Java object serialization
- writeParagraphVectors(ParagraphVectors, File) - Static method in class org.deeplearning4j.models.embeddings.loader.WordVectorSerializer
-
This method saves ParagraphVectors model into compressed zip file
- writeParagraphVectors(ParagraphVectors, String) - Static method in class org.deeplearning4j.models.embeddings.loader.WordVectorSerializer
-
This method saves ParagraphVectors model into compressed zip file located at path
- writeParagraphVectors(ParagraphVectors, OutputStream) - Static method in class org.deeplearning4j.models.embeddings.loader.WordVectorSerializer
-
This method saves ParagraphVectors model into compressed zip file and sends it to output stream
- writeSequenceVectors(SequenceVectors<T>, SequenceElementFactory<T>, String) - Static method in class org.deeplearning4j.models.embeddings.loader.WordVectorSerializer
-
This method saves specified SequenceVectors model to target file path
- writeSequenceVectors(SequenceVectors<T>, SequenceElementFactory<T>, File) - Static method in class org.deeplearning4j.models.embeddings.loader.WordVectorSerializer
-
This method saves specified SequenceVectors model to target file
- writeSequenceVectors(SequenceVectors<T>, SequenceElementFactory<T>, OutputStream) - Static method in class org.deeplearning4j.models.embeddings.loader.WordVectorSerializer
-
This method saves specified SequenceVectors model to target OutputStream
- writeSparseArray2D(OutputStream, int[][]) - Static method in class com.atilika.kuromoji.io.IntegerArrayIO
-
- writeSparseArray2D(OutputStream, String[][]) - Static method in class com.atilika.kuromoji.io.StringArrayIO
-
- writeStringToFile(String, String, JavaSparkContext) - Static method in class org.deeplearning4j.spark.util.SparkUtils
-
Write a String to a file (on HDFS or local) in UTF-8 format
- writeStringToFile(String, String, SparkContext) - Static method in class org.deeplearning4j.spark.util.SparkUtils
-
Write a String to a file (on HDFS or local) in UTF-8 format
- writeTsneFormat(Glove, INDArray, File) - Static method in class org.deeplearning4j.models.embeddings.loader.WordVectorSerializer
-
Write the tsne format
- writeTsneFormat(Word2Vec, INDArray, File) - Static method in class org.deeplearning4j.models.embeddings.loader.WordVectorSerializer
-
Write the tsne format
- writeVocabCache(VocabCache<VocabWord>, File) - Static method in class org.deeplearning4j.models.embeddings.loader.WordVectorSerializer
-
This method saves vocab cache to provided File.
- writeVocabCache(VocabCache<VocabWord>, OutputStream) - Static method in class org.deeplearning4j.models.embeddings.loader.WordVectorSerializer
-
This method saves vocab cache to provided OutputStream.
- writeWord2VecModel(Word2Vec, File) - Static method in class org.deeplearning4j.models.embeddings.loader.WordVectorSerializer
-
This method saves Word2Vec model into compressed zip file and sends it to output stream
PLEASE NOTE: This method saves FULL model, including syn0 AND syn1
- writeWord2VecModel(Word2Vec, String) - Static method in class org.deeplearning4j.models.embeddings.loader.WordVectorSerializer
-
This method saves Word2Vec model into compressed zip file and sends it to output stream
PLEASE NOTE: This method saves FULL model, including syn0 AND syn1
- writeWord2VecModel(Word2Vec, OutputStream) - Static method in class org.deeplearning4j.models.embeddings.loader.WordVectorSerializer
-
This method saves Word2Vec model into compressed zip file and sends it to output stream
PLEASE NOTE: This method saves FULL model, including syn0 AND syn1
- writeWordIds(String) - Method in class com.atilika.kuromoji.compile.TokenInfoDictionaryCompilerBase
-
- writeWordVectors(WeightLookupTable<T>, String) - Static method in class org.deeplearning4j.models.embeddings.loader.WordVectorSerializer
-
This method writes word vectors to the given path.
- writeWordVectors(WeightLookupTable<T>, File) - Static method in class org.deeplearning4j.models.embeddings.loader.WordVectorSerializer
-
This method writes word vectors to the given file.
- writeWordVectors(WeightLookupTable<T>, OutputStream) - Static method in class org.deeplearning4j.models.embeddings.loader.WordVectorSerializer
-
This method writes word vectors to the given OutputStream.
- writeWordVectors(ParagraphVectors, File) - Static method in class org.deeplearning4j.models.embeddings.loader.WordVectorSerializer
-
Deprecated.
- writeWordVectors(ParagraphVectors, String) - Static method in class org.deeplearning4j.models.embeddings.loader.WordVectorSerializer
-
Deprecated.
- writeWordVectors(Glove, File) - Static method in class org.deeplearning4j.models.embeddings.loader.WordVectorSerializer
-
This method saves GloVe model to the given output stream.
- writeWordVectors(Glove, String) - Static method in class org.deeplearning4j.models.embeddings.loader.WordVectorSerializer
-
This method saves GloVe model to the given output stream.
- writeWordVectors(Glove, OutputStream) - Static method in class org.deeplearning4j.models.embeddings.loader.WordVectorSerializer
-
This method saves GloVe model to the given OutputStream
- writeWordVectors(ParagraphVectors, OutputStream) - Static method in class org.deeplearning4j.models.embeddings.loader.WordVectorSerializer
-
Deprecated.
- writeWordVectors(InMemoryLookupTable, InMemoryLookupCache, String) - Static method in class org.deeplearning4j.models.embeddings.loader.WordVectorSerializer
-
Deprecated.
- writeWordVectors(Word2Vec, String) - Static method in class org.deeplearning4j.models.embeddings.loader.WordVectorSerializer
-
Deprecated.
- writeWordVectors(Word2Vec, File) - Static method in class org.deeplearning4j.models.embeddings.loader.WordVectorSerializer
-
Deprecated.
- writeWordVectors(Word2Vec, OutputStream) - Static method in class org.deeplearning4j.models.embeddings.loader.WordVectorSerializer
-
Deprecated.
- writeWordVectors(Word2Vec, BufferedWriter) - Static method in class org.deeplearning4j.models.embeddings.loader.WordVectorSerializer
-
Deprecated.
- WRONG - Static variable in class org.deeplearning4j.models.embeddings.reader.impl.BasicModelUtils
-
- WS_ALL_LAYERS_ACT - Static variable in class org.deeplearning4j.nn.graph.ComputationGraph
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Workspace for storing all layers' activations - used only to store activations (layer inputs) as part of backprop
Not used for inference
- WS_ALL_LAYERS_ACT - Static variable in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
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Workspace for storing all layers' activations - used only to store activations (layer inputs) as part of backprop
Not used for inference
- WS_ALL_LAYERS_ACT_CONFIG - Static variable in class org.deeplearning4j.nn.graph.ComputationGraph
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- WS_ALL_LAYERS_ACT_CONFIG - Static variable in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
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- WS_LAYER_ACT_1 - Static variable in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
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Next 2 workspaces: used for:
(a) Inference: holds activations for one layer only
(b) Backprop: holds activation gradients for one layer only
In both cases, they are opened and closed on every second layer
- WS_LAYER_ACT_2 - Static variable in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
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- WS_LAYER_ACT_X_CONFIG - Variable in class org.deeplearning4j.nn.graph.ComputationGraph
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- WS_LAYER_ACT_X_CONFIG - Variable in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
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- WS_LAYER_WORKING_MEM - Static variable in class org.deeplearning4j.nn.graph.ComputationGraph
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Workspace for working memory for a single layer: forward pass and backward pass
Note that this is opened/closed once per op (activate/backpropGradient call)
- WS_LAYER_WORKING_MEM - Static variable in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
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Workspace for working memory for a single layer: forward pass and backward pass
Note that this is opened/closed once per op (activate/backpropGradient call)
- WS_LAYER_WORKING_MEM_CONFIG - Variable in class org.deeplearning4j.nn.graph.ComputationGraph
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- WS_LAYER_WORKING_MEM_CONFIG - Variable in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
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- WS_RNN_LOOP_WORKING_MEM - Static variable in class org.deeplearning4j.nn.graph.ComputationGraph
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Workspace for working memory in RNNs - opened and closed once per RNN time step
- WS_RNN_LOOP_WORKING_MEM - Static variable in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
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Workspace for working memory in RNNs - opened and closed once per RNN time step
- WS_RNN_LOOP_WORKING_MEM_CONFIG - Static variable in class org.deeplearning4j.nn.graph.ComputationGraph
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- WS_RNN_LOOP_WORKING_MEM_CONFIG - Static variable in class org.deeplearning4j.nn.multilayer.MultiLayerNetwork
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